Environmental laws: the e↵ect on environmental outcomes in

an open economy

Inmaculada Martınez-Zarzoso

⇤, Thaıs Nunez-Rocha

†

July 25, 2017

Abstract

There is a vivid ongoing debate among environmental economists concerning theinstruments aiming to get a health environment. Solid environmental regulations in acountry could help to improve environmental quality. The main di�culty, however, is tofind a comparable measure of environmental regulation across countries. In this paper,we built an environmental regulation index, based on law-intensity variables specific toeach environmental topic. With this index we investigate the e↵ect of environmentallaws passed by countries on the respective environmental outcomes. We do this with amodel taking into account determinants of environmental quality and the simultaneitybetween environmental laws and outcomes with a panel data. Results confirm envi-ronmental laws intensity have an e↵ect improving environmental outcomes. This e↵ectis particular to the specific environmental outcome and the corresponding type of laws.

Keywords: Environmental outcomes, international trade, environmental

regulation, international environmental agreements, legislation, treaties,

log-linear and simultaneity.

JEL codes: F18, C33, C36, Q53, Q56.

⇤University Georg-August Goettingen, Chair of Development Economics.†University of Orleans Corresponding author : thais.nunez-rocha@univ-orleans.fr

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1 Introduction

The aim of this paper is to study the e↵ect of environmental laws on environmental out-comes, in order to determine if environmental regulations, in this case represented by laws,act as e�cient tools to improve the environment. We consider determinants of pollutionas income and trade openness e↵ects. Due to reverse causality from income and opennesswith the environmental outcomes, we use an instrumental variable procedure. There is alsoreverse causality between the environmental outcomes and the environmental regulation,we also address this issue.

There is a vivid ongoing debate among environmental economists concerning the instru-ments aiming to get a wholesome environment. Solid environmental regulations in a coun-try could suggest improvements in environmental quality.

Since the beginning of the past century, countries have been constructing them-selves withon an institutional basis. One of the main pillars of this basis is a legal frame. Laws havebeen shaped by the national institutionalism of countries and they also shed light on whatNations promote in terms of social priorities, cultural values, economic strategies and alsotheir environmental priorities.

Countries can express their priorities in their laws. Intensifying environmental regulationsshows an increase in environmental concern, and hence, could be measured as an increasein the number of environmental laws. The more a country devotes itself improving itsenvironmental outcomes, the more environmental laws it will pass. Conscious that theenforcement, or the quality of a law are also important, we also use a proxy variable totake this into account, in particular, we consider Government E↵ectiveness.

The pressure on the development of laws could also be initiated by agents’ demands. Anec-dotal evidence suggests that when the population feels that the quality of the environmentis deteriorating they start changing behaviour in order to take care of their living environ-ment and health.1 This could also lead to put pressure on governments in order to increaselaws protecting the environment.

The study of environmental legislation explores more in detail the e↵ect of environmentalregulation on the environmental performance of countries. But in addition, this allowsfor policy recommendation in terms of a trade o↵ between institutional e↵orts towards

1For more information about anecdotal evidence about China’s individual change in behaviourfor environmental threats to health please see: http://www.foodsafetynews.com/2014/07/chinas-food-safety-issues-are-worse-than-you-thought/.WAooDEeIBkQ (ChinaAos Food Safety Issues Worse ThanYou Thought and https://www.theguardian.com/sustainable-business/2015/may/14/china-middle-class-organics-food-safety-scares (China’s middle class turns to organics after food safety scares)

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environmental legislation development or the enforcement of the legislation. This is of cru-cial importance in the context of environmental protection, all the more so when choosingbetween di↵erent costly policy decisions, especially in developing countries.

This work evaluates the pay o↵ of devoting e↵orts in protecting the environment throughthe construction and development of a legal framework. More specifically, we assess theimpact of environmental laws on environmental outcomes, taking into account other de-terminants of pollution, as income and openness, and also the reverse causality involvedwith the explanatory variables and the outcomes. The environmental outcomes in studyare local air emissions, water pollution and forest area. The e↵ect of increasing levels ofpollution (or of environmental degradation) are going to be felt and hence could induce anincreasing demand for environmental quality and for more stringent regulations to enforceit. Specially when trade e↵ects are taken into account and also developed and developingcountries di↵erences (Ollivier (2016)). This is the first research to tackle the e↵ect of envi-ronmental regulation on environmental outcomes. We create, at a country-level setting, acomparable measure of environmental regulation as an index of environmental laws inten-sity, by environmental subject. This in a context in which regulations are the expressionsof governments’ priorities and agents’ demands for the protection of the environment incontrast to lobby pressure (Fredriksson et al. (2005)).

Additionally, this paper contributes methodologically speaking to overcoming the absenceof appropriate metrics across countries for an empirical approach (Dasgupta et al. (2002)).The variable of environmental regulation stringency that we construct adds an innovativeapproach about environmental regulation de jure (Brunel and Levinson (2013)). Whatis more, we include a panel data setting analysis which challenges previous results in theliterature.

Results show, that even if enforcement and environmental laws are important to improveenvironmental outcomes, only the e↵ect of environmental laws persists in all specifications.In addition, we challenge previous works proving trade being good for the environment(Frankel and Rose (2005)) showing an e↵ect of openness increasing water pollution anddecreasing forest area, the latter being particular to Non-OECD countries, and controllingby Forest transition.

The remainder of this paper is organised as follows. Section 2 discuses the relevant lit-erature on the determinants of pollution. Section 3 examines the e↵ect of environmentalregulation stringency on environmental outcomes. Section 4 introduces the environmentalregulation and section 5 explains the construction of the environmental regulation variable.Section 6 discusses the empirical strategy. The results are presented in section 7. Section8 concludes.

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2 Determinants of pollution

The impact of increasing international trade flows on environmental quality outcomes is anissue extensively discussed. The theoretical research has identified three main channels tostudy them: the scale, technique and composition e↵ects ((Copeland and Taylor (2003))).The two former e↵ects are expected to have, according to the theory, an unambiguousnegative and positive e↵ect on environmental quality, respectively. But additional to thesetwo, there is the composition e↵ect that is less straightforward to assess because it dependson the type of economy (Baghdadi et al. (2013)). In order to study this composition e↵ect,it is possible to break it down into its two driving forces: factor of endowments and/orenvironmental regulation di↵erences (Copeland and Taylor (2003)).

For a country having less strict environmental regulation vis-a-vis his trading partners,trade could have a negative e↵ect on the environment. Not only because countries couldgo towards dirty production (race to the bottom hypothesis), but because they can receivepollution of trade partners, either as a pollution haven e↵ect (Baghdadi et al. (2013),Cole (2004) and Ben Kheder and Zugravu (2012)) or as a waste haven e↵ect (Kellenberg(2012) and Kellenberg and Levinson (2014)). In contrast to this, countries reinforcingenvironmental regulation stringency could have positive e↵ects on trade by attracting cleanindustries (gains from trade hypothesis) (Vogel (2009), Porter and Van der Linde (1995),de Sousa et al. (2015) and Braithwaite and Drahos (2000)). Assessing the global e↵ect ofan open economy on the environment, apart from Frankel and Rose (2005) cross-sectionstudy, more extended research is still in short supply.

3 Environmental regulation e↵ects

The e↵ect of the environmental regulation has been studied in economics by adoptingdi↵erent perspectives as explained above. Their common denominator is to study thee↵ect that these regulations can have on di↵erent economic indicators such as consumption(Vogel (2009)), competitiveness (Ambec et al. (2013)), innovation (Hemmelskamp et al.(2013), Cole and Elliott (2003)), foreign direct investment (Fredriksson et al. (2003), Coleet al. (2006)), industry development (Ryan (2012), List et al. (2003)) among others. Inaddition there are also some policy related issues ranging from pollution havens (Gretheret al. (2012), Fredriksson and Millimet (2002)), industrial flight, environmental dumpingand race-to-the-bottom and to leakage e↵ect (Brunel and Levinson (2016)). However,the intuition behind a continuous increase in strictness in environmental regulation is toimprove environment (and health) outcomes. This is, however of extreme importance inorder to e�ciently allocate e↵orts to improve the environment.

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Some e↵orts have been made to study environmental regulations, in an open economy, at acountry level. Those studies use proxies of comparable measures such as managers’ percep-tion of environmental strictness (Kellenberg (2012)), institutional indexes (Ben Kheder andZugravu (2012) and Nunez-Rocha (2016)), treaties ratification (Kellenberg and Levinson(2014) and Nunez-Rocha (2016)) or regional trade agreements with environmental pro-visions (Baghdadi et al. (2013)). For OECD countries there is the work by Van Beersand Van Den Bergh (1997) that uses environmental pressure, environmental conditions orindicators of societal responses, among others.

Nevertheless, it is really hard to find in the literature a measure that reflects all aspectsof an environmental regulation in a country. This paper is an attempt to construct acomparable measure of environmental regulation at a country level, quantifying the numberof environmental laws. However, this approach has also some drawbacks. The first one isthe fact that we cannot distinguish whether the laws are outdated or modified. The secondone is the fact of countries concentrating on having better laws instead of having morelaws. And the third one is that in our variable, the Treaties’ date displayed is its date ofthe first negotiation meeting and not its date when enforcement starts. We mention thesedrawbacks in our paper as well as the way to deal with them.

The reason for including the environmental regulation, additionally, is also important froman Environmental Kuznets Curve (EKC) perspective. According to the EKC hypothesisemissions are positively correlated with income per capita at low levels of development,whereas when GDP per head increase, a threshold can be found after which emissionsdecrease with further increases of GDP per head. This results in a non-linear inverted U-shaped relationship between GDP per head and emissions. There is still no clear evidenceof the empirical illustration of EKC (Dinda (2004), Grossman and Krueger (1995), Lin andLiscow (2013), Stern (2004) and Copeland and Taylor (2004)).

Stern et al. (1996) criticise the existence of an EKC, and they underlined that the estimationprocedure is not straightforward due to a lack of production possibilities being modified dueto quality of the environment, and also the e↵ect of international trade on environmentaldegradation, and, last but not least, countries have di↵erent types of economies, whichtranslates on income e↵ects being di↵erent from one to another. In the empirical model,estimated in this paper, this e↵ect of increasing awareness about environmental issues withan increase in income, with the level and square GDP per capita variables introduced asdeterminants of the environmental outcomes.

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4 Environmental regulation as a legal framework

Preserving a clean environment is one of the biggest challenges that governments and theenvironmental international community face; evidence in other disciplines suggests thee↵ect of a legal framework on di↵erent outcomes.2 The economic activities of countries(production and trade) a↵ect the quality of the environment and a poor environmentcan threaten the health of a country’s inhabitants and also harm its wildlife. Passingenvironmental laws could be a way for decision makers to send a signal of the importancethey give to nature, hence, being an e↵ective way to protect the environment and fightagainst climate change Ruhl (2010).

Countries’ willingness to enjoy a clean environment could push decision-makers to fosterlaws towards this objective. Environmental treaties are also seen as promoters of thislegal frame, since they establish principles and then these principles are integrated incountries’ legislation. Proving an environmental legal framework being e↵ective, wouldbring to light how to target e↵orts towards enhancing a good environment. Although apolicy recommendation that suggests an increase in the number of laws passed to protectthe environment oversimplifies the complexity of the institutional structure to have anunpolluted and burgeoning nature. It nonetheless sheds light on the e�ciency of theselaws to maintain a sound environment.

Specifically, when studying environmental regulation stringency the literature concentrateson specific cases, either in some regions, or on some pollutants, and not always includingthe e↵ect of trade (Botta and Kozluk (2014), Brunel and Levinson (2016), Sauvage (2014),Copeland and Taylor (2003), Misra and Pandey (2005) Kellenberg (2009) and Pratt andMauri (2005).)

Homogeneous variables, that could serve to compare policies at a global level, are in shortsupply. The usefulness of such measures is that they would give the opportunity to raiseconclusions that can be suitable in a general way to any country. Nevertheless, in gen-eral the literature is forced to accept proxy variables that tackle one subject at a time,or that focus on one region or period. Hence, the di�culty of coming to more generalconclusions.

2Donohue and Levitt (2004) in Further Evidence that Legalised Abortion Lowered Crime show evidenceabout a causal link between legalised abortion and reductions in crime almost two decades later, when thecohorts exposed to legalised abortion reach their peak crime years. Also Acemoglu and Angrist (1999) inHow Large are Human-Capital Externalities? Evidence from Compulsory-Schooling Laws study the e↵ectof human capital on aggregate income, overcoming problems of identification with the use of instrumentalvariables. They estimate the e↵ect of the average schooling level in an individual’s state, using as aninstrument for average schooling the di↵erent compulsory attendance laws and child labor laws in U.S.states.

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In a scenario of globalisation when countries are trading with each other, ultimately whatwould be interesting to know, is if the environmental outcomes of countries, as a whole,are getting better when the number of number of environmental laws increases. This is ofespecial interest when confronted to trade with trade partners having di↵erent (stricter)environmental regulations (Dasgupta et al. (2002) and Grossman and Krueger (1994)).However, this is a defying task due to the arduousness to find a comparable measure ofenvironmental regulations among countries. The study of the impact of environmentalregulation on environmental outcomes should take into account the above-mentioned ef-fects, namely scale, technique and composition e↵ects, and deal with simultaneity betweenenvironmental laws and environmental outcomes, hence, this raises some challenges totackle.

In order to study the impact of environmental regulations on environmental outcomes, thedeparture point is to follow Baghdadi et al. (2013) and Martınez-Zarzoso and Maruotti(2011) to consider the main factors a↵ecting emissions and Frankel and Rose (2005) toaddress the e↵ect of openness on the environment, assessing simultaneity issues.

In a model a la Frankel and Rose (2005), using panel data, we add an environmentalregulation variable to specific to each country. This environmental regulation variable iscomposed of all countries’ legislation that could have an impact on the environment.

Our approach di↵ers from Frankel and Rose (2005) in three respects. We use panel data,we include an environmental regulation variable and we separate countries between OECDand Non-OECD. With our results we believe the positive e↵ect of trade on the environment,is not straightforward.

5 Defining environmental regulation

Environmental laws are the expression of di↵erent social, economic and global interests totackle a certain objective. But objectives are numerous, that is why these regulations arecharacterised by the fact that they work at di↵erent levels and with di↵erent scopes. Theliterature refers to this as multidimensionality (Brunel and Levinson (2016)).

In order to study these laws in their di↵erent spheres, we take into account a variable thatcontains each law that a country has passed, which is expected to have an environmentalpositive impact and we divide them into di↵erent subjects. Since environmental lawspromote also environmental management, the aim of studying these laws has arousedinterest of more than one actor, particularly in economies which are in transition. Wethink this sheds light on the e�ciency of this legal instrument, by subject.

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As a joint e↵ort of worldwide organisations such as the Food and Agriculture organisation(FAO), International Union for Conservation of Nature and Natural Resources (IUCN)and United Nations Environment Program (UNEP) a data-base is available in the form ofa compilation of environmental laws that countries passed in the last century. For moreinformation about the source of this variable please refer to Ecolex.

Environmental law is a discipline that was formally recognised thirty years ago, and hasbecome a major tool for sustainable development managing natural resources and theenvironment.3 According to our data up to 2015 168,401 environmental-laws have beenpassed in 137 countries. Laws can be classified depending on the political unit to whichthey apply: local, provincial, regional, national or supranational. On one hand, the mostpopular subjects of the treaties are Fisheries, Sea and Environmental General issues, whichis understandable because they are linked to the economic activity of fisheries and see spacemanagement which is one of the most important ancient economic activity, and this is alsodue to the raising importance that environmental issues have had in the passed years.Conversely, the most ancient (environmental) laws that we have here, are laws that areabout maritime regulations. E.g. a law that only allows a certain number of boats in aport. The main target of such a law is to ensure the good and e�cient functioning of theport. Nevertheless, since fewer (or limited number) of boats will be docking on at a givenport, as a positive externality there will be a decrease in see-water pollution.

The environmental regulation variable is composed of all environmental legislation passedin a country divided into subjects. As mentioned before, national laws are derived fromtreaties and some of the laws that this variable contains could also be formalisations oftreaties. Conscious of that, but nevertheless constrained to solve this issue, we assume thatsome of the laws are coming from international environmental negotiations, but since thelocal law creation is still part of the national e↵ort, we assume this should not distort ourresults.

Figure 1 shows the cumulative number of Treaties ratified by all countries in each yearsince 1830. Figure 2 shows the cumulative number of laws passed at a country level byyear. In both cases, for OECD and non-OECD countries and it can be observed, that mostlaws and treaties correspond to non-OECD countries. Especially when we see in Figure 1and 2 that there is a certain e↵ect on the national legislation following the treaties with acertain lag in time. However, a drawback of our treaties variable is that the date displayedin our data is the creation date of the treaty, not its date of enforcement. Not being able todisentangle this for the moment we focus on the study of the legislation or national laws.Even if this implies loosing a converge e↵ect that could be captured with the treaties’ typeof curve (Figure 2 right).

3ECOLEX: the Gateway to Environmental Law

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02

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8C

um. s

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s (h

undr

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1800 2000years

non-oecd oecd

Treaties

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4060

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um. s

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(hun

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1800 2000years

non-oecd oecd

Legislation

Figure 1: Legislation intensity by year 1830-2012

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1990 1995 2000 2005 2010 2015years

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1990 1995 2000 2005 2010 2015years

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Figure 2: Legislation intensity by year 1990-2012

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We define environmental national legislation as all the environmental laws. But also, somelaws that impact the environment positively even if it was not their original objective(e.g. A maritime law that has an objective to control the number of vessels on a portfor organisation or taxes purposes, will diminish the number of vessels and therefore theenvironmental pollution of them). laws passed in a country, along with the target or notof having an environmental impact, but actually potentially having one.

National laws are classified under a number of subjects: Agriculture, Air and atmosphere,Cultivated plants, Energy, Environment gen., Fisheries, Food and nutrition, Forestry, Landand soil, Livestock, Mineral resources, Sea, Waste and hazardous substances, Water, Wildspecies and ecosystem. The most targeted subject is Land and Soil with 288 laws as themaximum number that a country could possibly have passed in a year. Then, next inthe ranking we have Food and Nutrition, Cultivated Plants and Environmental GeneralIssues. Non-OECD countries are those having the biggest number of laws passed in oneyear in those issues and also in Forestry, Energy and Agricultural and rural development.The most common subjects for OECD countries are in order of importance: Fisheries,Livestock, Mineral resources, Water, Waste and hazardous substances, Air and atmosphereand Sea.

The way the variable is created is by adding the country-specific environmental laws byyear and by subject from 1830 to 2012.4 This variable is constructed as the cumulative sumof laws that a country passed from 1830 up to 2012. The data of environmental outcomesare shorter in time span. When doing the matching process, since this variable considers allthe laws of a country on an specific subject as the cumulative sum of all the periods before,the information about environmental laws previous to the year of study is considered asthe initial stock of laws, as environmental legal legacy.5

The matching process between the laws that are available and the respective outcomes de-serves further explanation. Table 1 shows the matching process of the specific laws to theircorrespondent environmental outcome. We use three outcomes of local air pollution: NO2,SO2 and PM 2.5. and also, an outcome of water pollution and a forest area index.

Table 31 shows the results for NO2 emissions. Since these emissions are mainly the resultof road tra�c and energy production, we can expect energy and air pollution laws to havea more important impact on these emissions.

For SO2 emissions, since they result from industrial processes, mainly coal and petroleumcombustion, we can expect mainly Air and atmosphere and Environmental general laws to

4The availability of the laws begins in 1830, nevertheless, the data of the environmental outcomes isonly available since 1990 for most countries.

5For more references about Indexes Based on Counts of Regulation see: Javorcik and Wei (2004) andJohnstone et al. (2010)

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outcome unit period

Air & atmosphere and Environment gen.

NOX

CO2 (equivalent)

1991-2008

SO2 1991-2008

PM 2,5 1995,2000,2005,2011

Water Water pollution kg per day 1991-2007

Environment gen. and Land & soil Forest area sq. km 2000-2012

Table 1: Matching of the laws with the environmental outcomes

have an impact.

In the case of PM 2.5, emissions are linked to the burning of fossil fuels in vehicles, powerplants and various industrial processes. We expect all three laws to have an impact,especially Environmental general issues.

Even though forest area is not an index of pollution, we think that it is interesting tosee the e↵ect of this outcome for two reasons. Firstly, because it allows to globally com-pare our results with the work of Frankel and Rose (2005). Secondly, according to Walker(1993) forest transitions are associated with social and economic transformations, due toindustrialisation and urbanisation, but also, the decrease of agricultural land use due toenvironmental legislation.6 The environmental laws that show significance in the estima-tions are those related to Land and Soil and Environmental in general. There are also lawsconcerning Forestry, but actually these laws mostly concentrate on forest management andtimber harvesting. In this work Forestry is a variable accounting for the Forest area insquare kilometres of a country. In this case, it is logical that a law targeting subjects asLand and Soil and general environmental issues should have significant e↵ects. For thesereasons we also think of using Forest area, as part of our environmental outcomes.

Figure 3 illustrates the intensity of the laws in these subjects around the world.

6 Empirical Strategy

6.1 Data and Variables

The explained variables are the environmental outcomes. These outcomes are in line withthe subjects of the laws. As local Air pollutants we use NO2, SO2 and PM2.5 emissions,

6Forest transition is assessed by the income e↵ect with the log of GDP per capita and the squared ofthe log of GDP per capita (Ln(GDPpercapita) and Ln(GDP

2percapita))

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[0,0](0,23](23,92](92,414](414,2208]No data

Air and atmosphere

[0,69](69,276](276,759](759,1518](1518,16744]No data

Environmental General

[0,92](92,276](276,644](644,1472](1472,8740]No data

Water

[0,0](0,161](161,506](506,1173](1173,6716]No data

Land and Soil

Figure 3: Legislation intensity by topic 1990-2012

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the units are kton (Gg) CO2 (equivalent) per year.7 For water quality we use organic waterpollutant emissions and for forests we use forest area in sq km.8

Variable Obs Mean Std. Dev. Min Max

Ln(NO2pc) 15611 -11.30173 1.058559 -14.8518 -6.54254Ln(SO2pc) 15638 -11.71123 1.360985 -14.91846 -7.986481Ln(PM2.5pc) 8903 -13.45328 1.529412 -17.26465 -9.285982Ln(Water pollution pc) 5092 -5.234484 .9439496 -11.49111 -4.174766Ln(Forest area pc) 15113 -5.922778 2.002903 -12.41062 -1.200452Laws by subjectEnvironmental general 953 44.52991 68.73646 1 753Air and atmosphere 947 13.44245 21.4775 0 186Energy 951 22.03365 45.09311 0 458Energy 951 22.03365 45.09311 0 458Forestry 953 34.35572 56.67444 0 706Land and soil 950 52.50105 77.8284 0 809Waste and haz. sub. 955 28.06911 44.37764 0 331Water 954 50.00314 60.90099 1 397All 15611 29.6701 58.96692 0 977

Ln(pred GDP) 10842 -5.676528 1.204951 -9.866512 -3.590374Ln(pred GDP)2 10842 33.67475 15.58148 12.89079 97.34807Ln(pred OPENNESS) 15611 4.109351 .3738489 3.345485 5.492424Ln(POP) 15611 16.2122 1.535514 13.00883 21.00939Ln(LANCAP) 15611 -4.017046 1.358202 -8.951666 -.4554439Gov. E↵ectiveness 15611 47.36686 28.73219 0 100

Table 2: Summary statistics

The explanatory variables are the same as in Frankel and Rose (2005). Nevertheless, inorder to include the environmental regulation stringency, we constructed as explained inthe last section, an index that reflects the environmental regulation intensity by country,as the cumulative sum of all environmental legislation (national laws), by environmentalsubject that 137 countries have from 2002-2012. 9 This could change depending on theenvironmental outcome, although we have constructed the regulation variable from 1830-

7Emissions are excluding short-cycle biomass burning (such as agricultural waste burning) and excludinglarge-scale biomass burning (forest fires, etc.)

8We take the FAO definition of Forest area. Forest Area is land under natural or planted stands of treesof at least 5 meters in situ, whether productive or not, and excludes tree stands in agricultural productionsystems (for example, in fruit plantations and agroforestry systems) and trees in urban parks and gardens.

9The period is restricted to the availability of all the other variables. Since we need a variable torepresent the enforcement. The best candidate that we find is from 2002-2012 period.

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2015 (to account for the initial stock of laws from countries). In the empirical analysis theperiod is determined by the availability of data for the dependent variable.

For more details about the period, refer to Table 1. A list with summary statistics of thevariables in found in 2. For a list of the sources of the variables, refer to Table 25.

6.2 Model specification

6.2.1 Determinants of environmental outcomes

According to Frankel and Rose (2005) we regress the ln(Env.Outcomepc)it environmentaloutcome (e.g. emissions, water pollution or forest area) explained by openness, income,population and the environmental regulation stringency as explanatory variables. We ex-pect income to have an e↵ect on increasing emissions but decreasing in time, expressed

with ln( ˆGDPpc2)it, showing the second part of the inverted-U shape curve. Population

e↵ect will vary depending on the group of countries and openness, we expect it to dependalso on the group of countries. Enforcement and Environmental regulations expressed bylaws are expected to decrease pollution and emissions.

ln(Env.Outcomepc)it = �0 + �1ln( ˆGDPpc)it + �2ln( ˆGDPpc2)it+

�3ln( ˆOPEN)it + �4ln(POP )it + �5ln(Gov.effec.)it+

�6(Env.Regulation)it + �7[(Gov.effec.)it ⇤ (Env.Regulation)it]

+FEi + FEt + µit

(1)

Our identification strategy is to use an interaction term between the enforcement and theenvironmental regulation variables ( [Ln(Gov.effectiveness.)it ⇤(Env.Regulation)it] ) in order to capture how many laws a country has passed and howwell they are being enforced. We expect the quality of institutions to be exogenous due tothe inclusion of country-time fixed e↵ects.

However, there could be reverse causality between the environmental regulation variableand the environmental outcomes, therefore additionally to our benchmark estimation, wealso test the model using an instrumental variable procedure in order to asses this simul-taneity between the environmental outcomes and the environmental regulation.

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(Env.Regulation)it = �0 + �1(Rule.law)it + µit (2)

Finding a variable that can be related with the intensity of environmental laws and inde-pendent from the environmental outcomes it is not a challenging procedure. Nevertheless,we search for a variable that could show the ease with which a country can pass laws. Thecandidates are institutional variables, we considered some indexes from WGI10 and alsothe Polity variable that shows the level of democracy of a country as in Frankel and Rose(2005). In order to find the most suitable one we investigate their performance in the firststage regressions but also the main concept that each of them are representing. Rule oflaw from the WGI seems to perform the best conceptually speaking. And we also observethat the results in regressions are as expected.11

We consider this variable to be the most suitable, because according to its definition fromWGI ”It reflects perceptions of the extent to which agents have confidence in and abideby the rules of society, and in particular the quality of contract enforcement, propertyrights, the police, and the courts, as well as the likelihood of crime and violence”. Alsothis variable might be correlated with law intensity. The rationale is that the more lawsa country has, the better the society perceives its institutions. In addition, the better acontract is enforced or the better courts and police function, is not necessarily correlatedwith the environmental outcomes.12

ln(Env.Outcomepc)it = �0 + �1ln( ˆGDPpc)it + �2ln( ˆGDPpc2)it+

�3ln( ˆOPEN)it + �4ln(Gov.effec.)it + �5( ˆEnv.Regulation)it+

FEi + FEt + µit

(3)

The other variables in use are: ln(Gov.effec.)it, Government E↵ectiveness is a variable

10Regulatory Quality: Reflects perceptions of the ability of the government to formulate and im-

plement sound policies and regulations that permit and promote private sector development. Voice and

Accountability: Reflects perceptions of the extent to which a country’s citizens are able to participatein selecting their government, as well as freedom of expression, freedom of association, and a free media.Rule of Law: Reflects perceptions of the extent to which agents have confidence in and abide by the rulesof society, and in particular the quality of contract enforcement, property rights, the police, and the courts,as well as the likelihood of crime and violence.

11Results on all the test available from the authors upon request.12It is worth noting that this variable also includes property rights assessment, there is research about

the impact of property rights on technology change. We point out that this is part of the technique e↵ectthat is taken into account in the model by the GDP variables and also by the country-subject fixed-e↵ects.

15

that takes into account the level of institutional quality that a country can have, understoodas quality of institutions.

This variable comes from World Governance Index (WGI). Its definition according to theWGI is Government e↵ectiveness: ”It reflects perceptions of the quality of public services,the quality of the civil service and the degree of its independence from political pressures, thequality of policy formulation and implementation, and the credibility of the government’scommitment to such policies.” We think this variable is a good candidate to show the en-forcement of the policies, due to its capacity of explaining the quality of institutions.

In Frankel and Rose (2005) specification, we also find the land capacity variable, but sincethis variable is time invariant, its e↵ect will be accounted for with the country dummies.FEi, FEt are the country-time fixed e↵ects and an idiosyncratic error term µit. We alsoadd the population ln(POP )it variable because we consider it to be an important factorof pollution, especially for emerging countries.13

(EnvironmentalRegulation)it is our variable of interest. To construct this variable wecreate a cumulative sum of laws from 1830-2015. This way we also take into accountthe initial stock of laws. Then, we separate our sample into three groups, namely all thecountries, OECD and non-OECD countries. The environmental law is used as one type oflaw in each estimation.

Note that ln( ˆGDPpc)it and ln( ˆOPEN)it are the predicted values of income and opennessrespectively. In Equation 1 we illustrate the determinants of pollution that explain thevariation within countries and over time. Nevertheless, it is also necessary to take intoaccount that there exist a reverse causality issue with income and openness. All otherthings remaining equal, when a country is polluting more due to increased production inpolluting activities, this increase in production is going to have an impact on increasingincome (technique and factor of endowment e↵ect). Also, if a country produces more inorder to grow and trade, the e↵ect of an increase in income and in openness leads to anincrease in pollution (scale e↵ect).

This generates a simultaneous causal e↵ect that should be corrected in order to give con-clusions about the e↵ect that laws could have on the environmental outcomes, and furtherinsights about the role of income and openness e↵ects.

Firstly, we estimate two first stage equations which predictions are used in the instrumentalvariable (IV) procedure as instruments for income and openness variables as equations 6and 8 state. These results are then put on Equation 1 which is then estimated with a

13In some specifications of the model this variable might, however, be collinear for this reason it doesnot appear on all tables

16

bootstrapped standard errors model. For more details about the first step estimationplease refer to: 10.

ln(GDP/POP )it = �0 + �1ln(POP )it + �2ln(GDPpc)i,t�1+

�3ln(I/GDP )it + �4nit + �5ln(school1)it + �6(school2)it + µit(4)

ln(tradeijt/GDPit) = �i + �j + 't + �1ln(POP )it + �2ln(POP )jt+

�3ln(Dist)ij + �4ln(Adj)ij�5(Area)ij + �6(Lang)ij + �7(Landborder)ij+

�8(Landlok)ij + �9ln(Landcapi/Landcapj)ij + �10ln(Remoteness)ij+

µijt

(5)

This instrument procedure helps to disentangle the endogeneity problem and also allows tocontrol for the scale and technique e↵ect, and, the factor of endowments (part of the compo-sition e↵ect). The predicted values are growth (ln( ˆGDPpc)it) and openness (ln( ˆOPEN)it)used in equation one.14

In our estimations we first determine the instrumental variable procedure for income andopenness. Then we focus on the interaction term of enforcement and environmental regu-lation. Later also we assess the endogeneity of environmental regulation within the envi-ronmental outcomes, these results are however less robust in general. For this reason weassume the hardness of the challenge to find the ideal instrument, and we use the interac-tion between the laws and their enforcement as our benchmark model and with it we dosome robustness test, but additionally we present the results of an instrumental variableestimation using two di↵erent instruments.

In robustness tests, we first estimate the e↵ect of excluding the countries considered feder-alists (Millimet (2003)),15 because those countries are passing laws at a federal level ratherthen a national level, this could bias results downwards. We also performed the IV pro-cedure using rule of law as an instrument model excluding the federalists, results are notso di↵erent from the IV procedure with all countries and rule of law as an instrument.We also test a specification to see if there is a particular e↵ect on the results coming fromemerging countries such as India and China. To do this we use the first model only withthese two countries, results appear to be non significant.16

14For results of first stage please refer to Appendix section 31 and 3215Federalist countries: Argentina, Australia, Austria, Bhutan, Brazil, Canada, Ethiopia, Germany, India,

Iraq, Lithuania, Malaysia, Mexico, Nigeria, Pakistan, Russian Federation, Sudan, United States of America,Venezuela Boliv. Rep. of

16Results available from the authors upon request.

17

Secondly, since the laws passed in one year could required time to be enforced, we test thisusing lagged values of the environmental laws and enforcement variables.

Finally, to assess the endogeneity of the intensity of laws with the outcomes, we follow thereasoning that environmental outcomes will possibly be a↵ected by laws concerned directlyor indirectly by their scope. Also, the intensity of laws should not be di↵erent from onesubject to another. We use food and nutrition laws as reasonable instrument variable,because their nature will be in fact correlated with the number of laws in our subject butnot necessarily correlated with air and water pollution and forest area.17 Significant resultsof all the above-mentioned estimations are commented in the next sections.

7 Results

7.1 NO2 emissions

A summary of the main results are in Table 3. For NO2 emissions significant results arefound in estimations of the model with the interaction term between the laws and theirenforcement (Table 8). Laws and their enforcement as a lag variable specification of themodel is in Table 26 and Instrumental Variable (IV) estimation, using food and nutritionas an instrument, is also estimated.18

Since these emissions are mainly a result of road tra�c and energy production, we expectenergy and air pollution laws to have a more important impact on these emissions. FromTable 8 we infer that a change in one unit the Environmental general issues laws decreasesNO2 emissions by 1.2% (column (3)) and a change in one unit in Air and atmospherelaws reduces NO2 pollution by 4.27% (column (9)). However, Energy related laws have nosignificant e↵ect. These e↵ects are exclusive to Non-OECD countries, and the enforcementvariable is non significant, neither it is the e↵ect of the interaction.

7.2 SO2 emissions

Table 4 shows the summary results for SO2 emissions. For SO2 emissions there are signif-icant results in all specifications of the model Tables 9, 14, 35 and 27.

17Only summary results for these estimations are presented, full results tables are available from theauthors upon request

18Results are available from the authors upon request

18

Since these emissions result from industrial processes, mainly coal and petroleum combus-tion, we expect Air and atmosphere laws to have an impact. In Table 9 the interaction ofthe Environmental laws joined with the enforcement results confirm this, showing that achange in one unit of Environmental general issues laws decrease SO2 emissions by 2.1%(Column (2)) but only in OECD countries. I also shows that, for a change in one unitof Energy laws, there is a decrease of SO2 emissions by 3.1% (Column (5)) for OECDcountries and less for Non-OECD countries 0.67% (Column (6)). As suspected for Air andatmosphere laws, a change in one unit decreases SO2 emissions for OECD and Non-OECDcountries by 3.25% (Column (8)) and 3.96% (Column (9)) respectively. Using an as aninstrument the Rule of law in the IV estimation, we assess the simultaneity between theEnvironmental laws and outcomes. Table 14 shows that enforcement variable increasesSO2 emissions; the environmental laws have no significant e↵ect, even with Rule of Law asinstrument.

7.3 PM2.5 emissions

For PM 2.5 emissions, Table 5 shows a summary of main results. These emissions are linkedto the burning of fossil fuels in vehicles, power plants and various industrial processes, sowe expect all three laws to have an impact. For PM2.5 emissions there are significantresults in all specifications of the model, shown in Tables 10, 15, 23 and 28.

Table 10 shows the interaction term of Laws and their enforcement. For each additionallaw in Energy laws there is a decrease in PM2.5 emissions by 0.6% (Column (5)) forOECD countries. There are also significant results concerning the interaction variable ofthe enforcement and the three subjects of the laws used for Air pollution. Nevertheless, itse↵ects is of smaller size (From 0,0242% and 0,0635%). There is also evidence of decreasinge↵ects on income, but this e↵ect is not robust to the division in OECD and Non-OECDcountries. Ln(POP ) has an e↵ect decreasing pollution, for Non-OECD countries.

In the IV estimation, with Rule of Law as an instrument, Table 15 shows e↵ects onlyon the determinants of pollution. Openness has an e↵ect decreasing pollution only forOECD countries. The e↵ect of the Ln(POP ) contrarily to what the first specification ofthe model shows, has an e↵ect decreasing PM2.5 emissions, the e↵ect is in two of the laws:Environmental general issues for OECD countries and Energy for Non-OECD.

7.4 Water pollution

For Water estimations Table 6 shows a summary of main results. For water pollution, weuse Organic water pollutants that are measured by biochemical oxygen demand (BOD),

19

which refers to the amount of oxygen that bacteria in water will consume in breaking downwaste. Water can be polluted for di↵erent reasons, we use laws in Environmental generalissues, Water and Waste and hazardous substances, expecting Water laws to have the mostimportant e↵ect. Full results are in Tables 11, 16, 24 and 29.

From Table 11, we observe that laws concerning Waste and hazardous substances have ane↵ect increasing water pollution. Nevertheless, these e↵ects do not hold when separatingOECD and Non-OECD countries. This might be explained because of the reverse causalitybetween the laws on Waste and hazardous substances and the pollution of Waste andhazardous substances. However, these e↵ects do not hold for the IV specifications. Andfor the determinants of pollution, there is a decreasing Water pollution income e↵ect, onlyfor OECD countries and an e↵ect of openness increasing Water pollution.

In the instrumental model with Rule of law Table 16. There are e↵ects decreasing Waterpollution from the Laws and their enforcement. Only enforcement has significant e↵ects.The instrument of the laws performs well for Water laws, yet the laws appear to decreasewater pollution, but the e↵ect is not significant. Income decreasing e↵ect is confirmed onlyfor OECD countries and openness appears to have a an increasing e↵ect on Water pollutionfor Non-OECD countries. There is a population e↵ect decreasing pollution but it does nothold for the separation between OECD and Non-OECD countries.

7.5 Forest area

Table 3 shows the summary results for Forest area. We expect laws on Forestry to havea positive e↵ect, but also laws related to Land and soil could have an e↵ect. All modelsshow some significant results and they are in Tables 12, 17, 25 and 30

In the first specification of the model Table 12, we observe population having an e↵ectincreasing Forest area, which makes sense for OECD countries because of Forest transition(Walker (1993)).

Using Rule of law as an instrument we find that it performs well, nevertheless, the laws’variables are not significant. Table 17.

20

Legislation on NO2 emissions

(1) (3) (9)LAWS Environment gen. Air and atmos.Countries all NON-OECD NON-OECDVARIABLES ln(NO2pc) ln(NO2pc) ln(NO2pc)

Env. Laws -0.00610* -0.0120** -0.0427**(0.00348) (0.00577) (0.0210)

Enforcement x Laws 0.000161* 0.000747**(8.35e-05) (0.000378)

Legislation on NO2 emissions lags(2) (3) (5) (7) (8) (9)

LAWS Environment gen. Energy Air and atmos.Countries OECD NON-OECD OECD all OECD NON-OECDVARIABLES ln(NO2pc) ln(NO2pc) ln(NO2pc) ln(NO2pc) ln(NO2pc) ln(NO2pc)

Enforcement (Gov. E↵.) t-1 0.00687* 0.00752** 0.00696*(0.00407) (0.00365) (0.00379)

Env. Laws t-1 -0.00844* -0.0156* -0.0406**(0.00494) (0.00864) (0.0201)

Enforcement x Laws t-1 0.000601*(0.000338)

Legislation on NO2 emissions food and nutrition as an instrument(1) (5) (7) (11)

LAWS Environment general EnergyCountries all NON-OECD all NON-OECDVARIABLES ln(NO2pc) ln(NO2pc) ln(NO2pc) ln(NO2pc)

Openness 1.427** 1.170* 1.470** 1.269*(0.656) (0.655) (0.666) (0.694)

Ln(POP) 1.516** 1.360* 1.437** 1.334*(0.661) (0.733) (0.634) (0.725)

Table 3: NO2 summary results

21

Legislation on SO2 emissions

(2) (5) (6) (7) (8) (9)LAWS Environment gen. Energy Energy Air and atmos. Air and atmos. Air and atmos.Countries OECD OECD NON-OECD all OECD NON-OECDVARIABLES ln(SO2pc) ln(SO2pc) ln(SO2pc) ln(SO2pc) ln(SO2pc) ln(SO2pc)

Environmental Laws -0.0210*** -0.0308* -0.00668** -0.0233*** -0.0352** -0.0396*(0.00745) (0.0159) (0.00326) (0.00875) (0.0158) (0.0205)

Enforcement x Laws 0.000238*** 0.000356** 0.000117* 0.000245** 0.000403** 0.000680*(8.17e-05) (0.000171) (6.64e-05) (9.74e-05) (0.000169) (0.000383)

Legislation on SO2 emissions rule of law as an instrument(3) (4)

LAWS Environment general Environment generalCountries OECDVARIABLES ln(SO2pc) 1st stage

Enforcement (Gover. E↵ect.) 0.0102**(0.00438)

Environmental Laws -0.00238(0.00370)

Rule of Law -0.929**(0.410)

Legislation on SO2 emissions without federalist countries(1) (2) (7) (8) (9)

LAWS Environment gen. Environment gen. Air and atmos. Air and atmos. Air and atmos.Countries all OECD all OECD NON-OECDVARIABLES ln(SO2pc) ln(SO2pc) ln(SO2pc) ln(SO2pc) ln(SO2pc)

Environmental Laws -0.00891* -0.0202** -0.0256** -0.0315* -0.0430*(0.00486) (0.00978) (0.0103) (0.0174) (0.0256)

Enforcement x Laws 0.000227** 0.000260** 0.000355*(0.000109) (0.000119) (0.000193)

Legislation on SO2 emissions lagged environmental lawsLAWS Environment gen. Energy Air and atmos.Countries all OECD OECD all OECD NON-OECDVARIABLES ln(SO2pc) ln(SO2pc) ln(SO2pc) ln(SO2pc) ln(SO2pc) ln(SO2pc)Ln(GDPpc)2 -0.0192* -0.0645** -0.0572* -0.0182* -0.0544*

(0.0106) (0.0285) (0.0306) (0.0108) (0.0299)Environmental Laws t-1 -0.0275*** -0.0402* -0.0268*** -0.0399* -0.0432**

(0.00857) (0.0209) (0.00879) (0.0209) (0.0193)Enforcement x Laws t-1 0.000305*** 0.000446** 0.000267*** 0.000441* 0.000702**

(9.40e-05) (0.000223) (9.61e-05) (0.000226) (0.000338)

Legislation on SO2 emissions food and nutrition as an instrument(1) (2) (5) (7) (8) (11)

LAWS Environment general Environment general Energy EnergyCountries all NON-OECD all NON-OECDVARIABLES ln(SO2pc) 1st stage ln(SO2pc) ln(SO2pc) 1st stage ln(SO2pc)

Ln(POP) 1.608** 1.299* 1.239** 1.284*(0.727) (0.716) (0.601) (0.685)

Environmental Laws 0.00617 0.00119 0.0107 0.00255(0.00468) (0.00279) (0.00870) (0.00560)

Environmental Laws (Food) 0.113* 0.0619*(0.0617) (0.0316)

Table 4: SO2 summary results

22

Legislation on PM2.5 emissions interaction of enforcement and laws

(1) (3) (4) (5) (6) (7) (9)LAWS Environment gen. Environment gen. Energy Energy Energy Air and atmos. Air and atmos.Countries all NON-OECD all OECD NON-OECD all NON-OECDVARIABLES ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc)

Ln(GDPpc)2 -0.00532*** -0.00577*** -0.00553***(0.00191) (0.00188) (0.00187)

Ln(POP) 0.683*** 0.803*** 0.647*** 0.756*** 0.645*** 0.775***(0.127) (0.193) (0.120) (0.196) (0.182)

Environmental Laws 0.00210* -0.00596**(0.00118) (0.00296) (0.00299)

Enforcement x Laws -2.42e-05** -3.13e-05* 6.35e-05* -6.11e-05*(1.11e-05) (1.66e-05) (3.44e-05) (3.34e-05)

Legislation on PM2.5 emissions Rule of Law as an instrument(3) (7) (11) (15)

Laws Environment general Energy Energy Air and atmosphereCountries OECD all NON-OECD OECDVARIABLES ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc)

Openness -1.841**(0.786)

Ln(POP) -0.824*** -0.978* -1.184* -0.693*(0.225) (0.581) (0.658) (0.356)

Legislation on PM2.5 emissions Federalists countries(1) (3) (4) (7) (8) (9)

LAWS Environment gen. Energy Air and atmos.Countries all NON-OECD all all OECD NON-OECDVARIABLES ln(PMpc) ln(PMpc) ln(PMpc) ln(PMpc) ln(PMpc) ln(PMpc)

Ln(GDPpc)2 -0.00291** -0.00367*** -0.00418***(0.00139) (0.00139) (0.00132)

Ln(POP) 0.639*** 0.766*** 0.610*** 0.585*** 0.768***(0.123) (0.175) (0.129) (0.126) (0.151)

Enforcement (Gover. E↵ect.) 0.00264** 0.00228** 0.00223** 0.00211** 0.00621* 0.00184*(0.00103) (0.00114) (0.00106) (0.000992) (0.00326) (0.00104)

Environmental Laws 0.00336*** 0.00378** 0.00290*** 0.00788** 0.0193***(0.00112) (0.00149) (0.00111) (0.00380) (0.00605)

Enforcement x Laws -4.85e-05*** -5.70e-05** -4.52e-05*** -0.000104** -0.000301***(1.44e-05) (2.70e-05) (1.58e-05) (4.80e-05) (0.000103)

Legislation on PM2.5 emissions lagged environmental laws(1) (2) (3) (4) (5) (6) (7) (8) (9)

LAWS Environment gen. Energy Air and atmos.Countries all OECD NON-OECD all OECD NON-OECD all OECD NON-OECDVARIABLES ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc)

Ln(GDPpc)2 -0.0105*** -0.00639* -0.0106*** -0.00779** -0.0110*** -0.00676*(0.00275) (0.00375) (0.00256) (0.00351) (0.00265) (0.00375)

Ln(POP) -0.838*** -1.045*** -0.775*** -0.964*** -0.783*** -1.032***(0.144) (0.132) (0.308) (0.135) (0.314)

Enforcement (Gover. E↵ect.) t-1 0.00277** 0.00287** 0.00263** 0.00255* 0.00253** 0.00602* 0.00267**(0.00123) (0.00146) (0.00117) (0.00142) (0.00122) (0.00336) (0.00132)

Environmental Laws t-1 0.00153*(0.000854)

Enforcement x Laws t-1 -2.38e-05*(1.33e-05)

Legislation on PM2.5 emissions Food and nutrition laws as as instrument(3) (7) (9) (11)

LAWS Environment general Energy Energy EnergyCountries OECD all OECD NON-OECDVARIABLES ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc) ln(PM2.5pc)

Openness -1.841** -1.652*(0.786) (0.948)

Ln(POP) -0.824*** -0.989* -1.194*(0.225) (0.597) (0.665)

Table 5: PM summary results

Leg

islation

on

waterpollution

intera

ction

ofen

forcem

entand

environmen

tallaws

(1)

(4)

(5)

(7)

LAW

SEnv

iron

mentgeneral

Water

Water

Waste

andhazardou

ssubstan

ces

Countries

all

all

OECD

all

VARIA

BLES

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

Ln(G

DPpc)

2-0.0253*

(0.0137)

Open

ness

2.458**

2.885***

2.532**

(1.001)

(1.099)

(0.996)

Environmen

talLaw

s0.00609**

(0.00307)

Enforcem

entxLaw

s-6.23e-05*

(3.70e-05)

Leg

islation

on

waterpollution

rule

oflaw

asan

instru

men

t(3)

(5)

(7)

(8)

(13)

(15)

Law

sEnv

iron

mentgeneral

Env

iron

mentgeneral

Water

Water

Waste

andhazardou

ssubstan

ces

Waste

andhazardou

ssubstan

ces

Cou

ntries

OECD

NON-O

ECD

all

all

OECD

VARIA

BLES

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

1ststage

ln(W

at.poll.pc)

ln(W

at.poll.pc)

Ln(G

DPpc)

2-0.0211*

-0.0202*

(0.0115)

(0.0108)

Open

ness

2.482**

(1.039)

Ln(P

OP)

-0.994*

-1.079*

(0.579)

(0.646)

Environmen

talLaw

s-0.00683

(0.00744)

Rule

ofLaw

-0.318*

(0.187)

Leg

islation

on

waterpollution

withoutFed

eralist

countries

(1)

(4)

(7)

LAW

SEnv

iron

mentgeneral

Water

Waste

andhazardou

ssubstan

ces

Countries

all

all

all

VARIA

BLES

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

Open

ness

2.941**

3.036**

2.703***

(1.153)

(1.201)

(0.984)

Environmen

talLaw

s0.00715**

(0.00306)

Enforcem

entxLaw

s-7.68e-05**

(3.84e-05)

Leg

islation

on

waterpollution

lagged

environmen

talre

gulation

(5)

(7)

LAW

SWater

Waste

andhazardou

ssubstan

ces

Countries

OECD

all

VARIA

BLES

ln(N

O2p

c)ln(N

O2p

c)

Ln(G

DPpc)

2-0.0324*

(0.0169)

Environmen

talLaw

st-1

0.00929*

(0.00479)

Enforcem

entxLaw

st-1

-9.97e-05*

(5.60e-05)

Leg

islation

on

waterpollution

Food

and

nutrition

lawsasan

instru

men

t(1)

(5)

(7)

(11)

(13)

(15)

(17)

LAW

SEnv

iron

mentgeneral

Env

iron

mentgeneral

Water

Water

Waste

andhazardou

ssubstan

ces

Waste

andhazardou

ssubstan

ces

Waste

andhazardou

ssubstan

ces

Cou

ntries

all

NON-O

ECD

all

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

Ln(G

DPpc)

2-0.0218***

(0.00835)

Open

ness

3.044***

2.031**

2.566***

1.708**

2.551***

1.630**

(0.923)

(0.813)

(0.934)

(0.705)

(0.828)

(0.733)

Ln(P

OP)

-0.828*

(0.499)

Table6:Waterpollutionsummary

results

Leg

islation

on

Fore

stare

aintera

ction

ofen

forcem

entwith

laws

(1)

(2)

(4)

(5)

(7)

(8)

LAW

SEnv

iron

mentgeneral

Env

iron

mentgeneral

Forestry

Forestry

Lan

dan

dsoil

Lan

dan

dsoil

Countries

all

OECD

all

OECD

all

OECD

VARIA

BLES

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

Ln(P

OP)

1.25

2***

1.10

2***

1.25

4***

1.09

3***

1.24

8***

1.09

4***

(0.128

)(0.139

)(0.134

)(0.113

)(0.135

)(0.124

)

Leg

islation

on

Fore

stare

aru

leoflaw

asan

intrumen

t(1)

(2)

(5)

(6)

(7)

(8)

(11)

(12)

(17)

(18)

Environmen

tgen

eral

Fore

stry

all

NON-O

ECD

all

NON-O

ECD

NON-O

ECD

NON-O

ECD

VARIA

BLES

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

Open

ness

-0.225

*-0.188

*-0.219

*-0.186

*-0.173

*(0.123

)(0.100

)(0.115

)(0.099

4)(0.089

8)Ln(P

OP)

-1.286

***

-1.308

***

-1.285

***

-1.305

***

-1.297

***

(0.155

)(0.182

)(0.161

)(0.185

)(0.171

)Environmen

talLaw

s-0.000

188

-0.000

379

-0.000

205

-0.000

386

-0.000

409

(0.000

680)

(0.000

705)

(0.000

790)

(0.000

753)

(0.000

796)

Rule

oflaw

0.85

0**

0.97

3**

0.72

8*0.91

2*0.88

8*(0.347

)(0.406

)(0.435

)(0.510

)(0.455

)

Leg

islation

on

Fore

stare

awithoutFed

eralist

countries

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

LAW

SEnvironmen

tgen

.Fore

stry

Land

and

Soil

Countries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

VARIA

BLES

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

Ln(G

DPpc)2

-0.005

16*

-0.005

71**

(0.002

94)

(0.002

63)

Ln(P

OP)

1.22

6***

0.92

0***

1.22

6***

0.95

9***

1.23

5***

0.98

0***

(0.126

)(0.131

)(0.135

)(0.141

)(0.138

)(0.140

)Enforcem

ent(G

over

.E↵ec

t.)

-0.000845*

-0.000126

-0.00164**

-0.00135**

-0.00206***

(0.000

497)

(0.001

05)

(0.000

721)

(0.000

538)

(0.000

691)

Environmen

talLaw

s-0.00151*

-0.00285**

-0.00437***

-0.00622***

(0.000

780)

(0.001

13)

(0.001

47)

(0.001

76)

Enforcem

entxLaw

s2.10e-05**

4.59e-05**

5.95e-05***

9.28e-05***

(9.97e-06)

(1.80e-05)

(1.99e-05)

(2.57e-05)

Leg

islation

on

Fore

stare

alagged

ofen

vironmen

talre

gulation

(3)

(6)

(9)

LAW

SEnv

iron

mentgeneral

Forestry

Lan

dan

dsoil

Countries

NON-O

ECD

NON-O

ECD

NON-O

ECD

VARIA

BLES

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

Ln(P

OP)

-1.251

***

-1.251

***

-1.237

***

(0.176

)(0.180

)(0.173

)

Leg

islation

on

Fore

stare

aFood

and

nutrition

asan

instru

men

t(1)

(3)

(5)

(7)

(9)

(11)

(13)

(15)

(16)

(17)

LAW

SEnvironmen

tgen

eral

Environmen

tgen

eral

Environmen

tgen

eral

Environmen

tgen

eral

Fore

stry

Fore

stry

Land

and

soil

Land

and

soil

Land

and

soil

Land

and

soil

Countries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

OECD

NON-O

ECD

VARIA

BLES

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

Open

ness

-0.216

*-0.266

*-0.181

**-0.220

*-0.371

*-0.182

**-0.220

*-0.312

*-0.184

**(0.111

)(0.155

)(0.090

9)(0.113

)(0.208

)(0.090

9)(0.112

)(0.160

)(0.091

5)Ln(P

OP)

-1.242

***

-1.220

***

-1.226

***

-1.253

***

-1.179

***

-1.223

***

-1.252

***

-1.178

***

-1.228

***

(0.109

)(0.249

)(0.136

)(0.110

)(0.183

)(0.149

)(0.091

5)(0.149

)(0.125

)Environmen

talLaw

s0.00

0118

(0.000

173)

Environmen

talLaw

s(F

ood)

0.53

9**

(0.236

)

Table7:Forest

areasummary

results

NO2EM

ISSIO

NS

Leg

islation

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

LAW

SEnvironmen

tgen

eral

Ener

gy

Air

and

atm

os.

Countries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)

Ln(G

DPpc)?

0.598

1.498

0.768

0.547

1.372

0.711

0.589

1.374

0.819

(0.750)

(1.642)

(0.992)

(0.727)

(1.493)

(0.984)

(0.739)

(1.697)

(1.025)

Ln(G

DPpc)

2?

0.0445

0.169

0.0559

0.0424

0.155

0.0534

0.0430

0.156

0.0573

(0.0678)

(0.187)

(0.0793)

(0.0659)

(0.169)

(0.0788)

(0.0664)

(0.188)

(0.0823)

Openness

1.374

0.00668

1.122

1.459

-0.0735

1.375

1.102

0.0809

0.849

(1.189)

(1.676)

(1.601)

(1.099)

(1.798)

(1.790)

(1.250)

(1.425)

(1.369)

Ln(P

OP)

1.184

0.990

0.952

1.317

0.931

1.163

1.160

0.924

1.096

(0.868)

(1.313)

(1.022)

(0.848)

(1.469)

(0.992)

(0.885)

(1.361)

(1.056)

Enforcem

ent(G

over

.E↵ec

t.)

-0.00790

-0.00487

-0.00948

-0.00673

-0.00606

-0.00832

-0.00786

-0.00427

-0.00990

(0.00637)

(0.00892)

(0.00779)

(0.00605)

(0.00836)

(0.00767)

(0.00583)

(0.00833)

(0.00764)

Environmen

talLaw

s-0.00610*

-0.000265

-0.0120**

0.000310

-0.00297

-0.00550

-0.0101

0.000333

-0.0427**

(0.00348)

(0.00813)

(0.00577)

(0.00322)

(0.0145)

(0.00558)

(0.00821)

(0.0132)

(0.0210)

Enforcem

entxLaw

s6.20e-05

9.89e-06

0.000161*

-6.74e-06

3.10e-05

0.000108

0.000106

1.12e-05

0.000747**

(4.28e-05)

(8.89e-05)

(8.35e-05)

(5.00e-05)

(0.000155)

(0.000109)

(9.09e-05)

(0.000143)

(0.000378)

Observations

679

208

471

680

208

472

677

208

469

R-squ

ared

0.073

0.218

0.089

0.067

0.217

0.077

0.070

0.219

0.088

Number

ofis

126

3195

126

3195

126

3195

Countrysectorand

timedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Bootstrapped

standard

erro

rsYES

YES

YES

YES

YES

YES

YES

YES

YES

Table8:LegislationonNO2

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.In

theis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Airan

dAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

e.

26

SO2EM

ISSIO

NS

Leg

islation

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

LAW

SEnvironmen

tgen

eral

Ener

gy

Air

and

atm

os.

Countries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)

Ln(G

DPpc)?

0.09

640.02

510.07

280.08

330.00

436

0.06

050.10

60.00

867

0.09

01(0.152

)(0.098

1)(0.197

)(0.162

)(0.092

9)(0.196

)(0.162

)(0.096

0)(0.206

)Ln(G

DPpc)

2?

-0.012

4-0.039

60.00

0273

-0.010

8-0.036

10.00

0902

-0.009

61-0.035

70.00

198

(0.009

35)

(0.027

5)(0.012

5)(0.009

65)

(0.026

7)(0.012

0)(0.009

75)

(0.026

6)(0.012

3)Open

ness

0.77

10.47

70.48

30.81

00.46

10.61

70.85

50.56

00.55

7(0.997

)(1.622

)(1.266

)(1.203

)(1.728

)(0.588

)(1.344

)(1.596

)(1.402

)Ln(P

OP)

1.13

7-0.177

1.16

31.23

4*0.37

11.20

00.89

2-0.159

1.03

6(0.707

)(1.355

)(0.895

)(0.734

)(1.545

)(0.838

)(0.720

)(1.366

)(0.943

)Enforcem

ent(G

over

.E↵ec

t.)

-0.005

65-0.004

10-0.008

14-0.004

630.00

117

-0.007

51-0.006

25-0.002

41-0.008

80(0.005

97)

(0.008

14)

(0.006

85)

(0.006

01)

(0.007

73)

(0.006

71)

(0.006

08)

(0.008

29)

(0.007

08)

Environmen

talLaw

s-0.005

44-0.0210***

-0.007

69-0.001

62-0.0308*

-0.00668**

-0.0233***

-0.0352**

-0.0396*

(0.004

14)

(0.007

45)

(0.005

33)

(0.002

64)

(0.015

9)(0.003

26)

(0.008

75)

(0.015

8)(0.020

5)Enforcem

entxLaw

s5.84

e-05

0.000238***

0.00

0115

1.25

e-05

0.000356**

0.000117*

0.000245**

0.000403**

0.000680*

(4.79e-05)

(8.17e-05)

(8.00e-05)

(4.33e-05)

(0.000

171)

(6.64e-05)

(9.74e-05)

(0.000

169)

(0.000

383)

Observations

679

208

471

676

208

468

680

208

472

R-squ

ared

0.08

50.53

50.08

10.07

90.50

60.07

90.09

20.53

10.08

6Number

ofis

125

3194

125

3194

126

3195

Countrysectorand

timedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Bootstrapped

standard

erro

rsYES

YES

YES

YES

YES

YES

YES

YES

YES

Table9:LegislationonSO2

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.In

theis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Airan

dAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

e.

27

PM

2.5

EM

ISSIO

NS

Leg

islation

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

LAW

SEnvironmen

tgen

eral

Ener

gy

Air

and

atm

os.

Countries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(P

M2.5p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)

Ln(G

DPpc)?

-0.00317

0.0282

-0.0147

0.00164

0.0322

-0.0124

0.00162

0.0141

-0.0138

(0.0269)

(0.0497)

(0.0307)

(0.0254)

(0.0541)

(0.0290)

(0.0272)

(0.0511)

(0.0288)

Ln(G

DPpc)

2?

-0.00532***

-0.00643

-0.00159

-0.00577***

-0.00744

-0.00210

-0.00553***

-0.00554

-0.00204

(0.00191)

(0.00583)

(0.00202)

(0.00188)

(0.00537)

(0.00203)

(0.00187)

(0.00573)

(0.00221)

Openness

-0.0746

-1.175

-0.0820

-0.126

-0.902

-0.151

-0.105

-1.134

-0.0950

(0.248)

(0.749)

(0.508)

(0.246)

(0.703)

(0.587)

(0.251)

(0.758)

(0.565)

Ln(P

OP)

0.683***

0.803***

0.647***

0.756***

0.645***

0.775***

(0.127)

(0.193)

(0.120)

(0.196)

(0.121)

(0.182)

Enforcem

ent(G

over

.E↵ec

t.)

0.00164

0.00436

0.00133

0.00143

0.00335

0.00113

0.00115

0.00453

0.000942

(0.00106)

(0.00292)

(0.00122)

(0.00112)

(0.00252)

(0.00120)

(0.00105)

(0.00339)

(0.00109)

Environmen

talLaw

s0.00134

-0.00268

0.00128

0.00210*

-0.00596**

0.00197

0.00430

-0.00335

0.00903

(0.000891)

(0.00196)

(0.00158)

(0.00118)

(0.00296)

(0.00191)

(0.00299)

(0.00391)

(0.00657)

Enforcem

entxLaw

s-2.42e-05**

2.51e-05

-2.52e-05

-3.13e-05*

6.35e-05*

-3.02e-05

-6.11e-05*

3.10e-05

-0.000147

(1.11e-05)

(2.18e-05)

(3.09e-05)

(1.66e-05)

(3.44e-05)

(3.55e-05)

(3.34e-05)

(4.24e-05)

(0.000123)

Observations

378

120

258

376

120

256

377

120

257

R-squ

ared

0.639

0.860

0.585

0.647

0.864

0.599

0.634

0.854

0.589

Number

ofis

122

3191

121

3190

121

3190

Countrysectorand

timedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Bootstrapped

standard

erro

rsYES

YES

YES

YES

YES

YES

YES

YES

YES

Table10:LegislationonPM2.5

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.In

theis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Airan

dAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

e.

28

WATER

POLLUTIO

NLeg

islation

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

LAW

SEnvironmen

tgen

eral

Water

Wasteand

haza

rdoussu

bstance

sCountries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

Ln(G

DPpc)?

0.00919

-0.0116

-0.0584

0.00718

-0.0157

-0.0632

0.00542

-0.0188

-0.0589

(0.0678)

(0.0912)

(0.113)

(0.0646)

(0.0856)

(0.113)

(0.0648)

(0.0862)

(0.121)

Ln(G

DPpc)

2?

-0.00123

-0.0209

0.00964

-0.00353

-0.0253*

0.00686

-0.00201

-0.0186

0.00860

(0.00889)

(0.0137)

(0.0141)

(0.00838)

(0.0137)

(0.0132)

(0.00829)

(0.0144)

(0.0121)

Openness

2.458**

1.894

1.728

2.885***

1.797

2.101

2.532**

2.152

1.733

(1.001)

(3.266)

(1.071)

(1.099)

(2.946)

(1.590)

(0.996)

(2.975)

(1.267)

Ln(P

OP)

-0.825

-1.103

-0.601

-0.895

-1.010

-0.600

-0.796

-1.175

-0.533

(0.660)

(1.567)

(0.846)

(0.671)

(1.682)

(0.874)

(0.668)

(1.664)

(0.853)

Enforcem

ent(G

over

.E↵ec

t.)

-0.000328

-0.00122

-0.000133

-0.00100

-0.00155

-0.00145

0.000819

0.000252

-0.000484

(0.00229)

(0.00672)

(0.00314)

(0.00230)

(0.00689)

(0.00356)

(0.00233)

(0.00595)

(0.00308)

Environmen

talLaw

s0.000610

0.00390

0.000650

0.000402

0.00279

-0.00104

0.00609**

0.00521

0.00425

(0.00187)

(0.00946)

(0.00254)

(0.00290)

(0.00640)

(0.00489)

(0.00307)

(0.00533)

(0.0101)

Enforcem

entxLaw

s-5.24e-06

-3.16e-05

-1.13e-05

6.10e-06

-1.14e-05

2.60e-05

-6.23e-05*

-4.63e-05

-5.35e-05

(2.27e-05)

(0.000103)

(4.91e-05)

(3.30e-05)

(7.29e-05)

(8.92e-05)

(3.70e-05)

(6.01e-05)

(0.000144)

Observations

248

119

129

247

119

128

249

119

130

R-squ

ared

0.240

0.462

0.182

0.263

0.489

0.202

0.271

0.484

0.184

Number

ofis

6326

3763

2637

6326

37Countrysectorand

timedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Bootstrapped

standard

erro

rsYES

YES

YES

YES

YES

YES

YES

YES

YES

Table11:LegislationonWaterpollution

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.In

theis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Airan

dAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

e.

FOREST

AREA

Leg

islation

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

LAW

SEnvironmen

tgen

.Fore

stry

Land

and

soil

Countries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

Ln(G

DPpc)?

0.0259

-0.0308

0.0365

0.0240

-0.021

20.03

570.02

31-0.022

30.03

38(0.0286)

(0.0229)

(0.0311)

(0.0274)

(0.021

4)(0.032

0)(0.027

9)(0.024

1)(0.031

2)Ln(G

DPpc)

2?

-0.000328

0.000725

-0.00242

3.26e-05

0.00

0544

-0.002

420.00

0371

0.00

0690

-0.002

16(0.00197)

(0.00282)

(0.00268)

(0.00191)

(0.002

87)

(0.002

77)

(0.002

03)

(0.002

88)

(0.002

73)

Openness

-0.214

-0.264

-0.193

-0.220

-0.203

-0.189

-0.220

-0.250

-0.184

(0.276)

(0.222)

(0.624)

(0.309)

(0.236

)(0.689

)(0.313

)(0.234

)(0.578

)Ln(P

OP)

1.252***

1.102***

1.254***

1.09

3***

1.24

8***

1.09

4***

(0.128)

(0.139)

(0.134)

(0.113

)(0.135

)(0.124

)Enforcem

ent(G

over

.E↵ec

t.)

0.000266

-2.83e-05

-1.42e-05

0.000335

0.00

0450

-4.86e-05

0.00

0497

0.00

0214

0.00

0290

(0.000603)

(0.000881)

(0.000732)

(0.000576)

(0.000

978)

(0.000

753)

(0.000

613)

(0.000

952)

(0.000

774)

Environmen

talLaw

s-0.000398

0.00111

-0.000639

-0.000369

0.00

208

-0.000

791

7.11

e-05

0.00

126

3.68

e-05

(0.000458)

(0.00105)

(0.000771)

(0.00121

)(0.001

82)

(0.001

75)

(0.000

554)

(0.001

26)

(0.000

698)

Enforcem

entxLaw

s7.12e-06

-1.13e-05

1.37e-05

7.01e-06

-2.45e-05

1.82

e-05

1.62

e-07

-1.38e-05

2.20

e-06

(5.63e-06)

(1.19e-05)

(1.24e-05)

(1.41e-05)

(2.00e-05)

(2.49e-05)

(5.93e-06)

(1.34e-05)

(1.13e-05)

Observations

657

210

447

654

210

444

658

210

448

R-squ

ared

0.668

0.728

0.677

0.664

0.73

10.67

50.66

50.72

60.67

5Number

ofis

121

3190

122

3191

122

3191

Countrysectorand

timedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Bootstrapped

standard

erro

rsYES

YES

YES

YES

YES

YES

YES

YES

YES

Table12:LegislationonForest

area

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.In

theis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Airan

dAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

e.

NO2EM

ISSIO

NS

(1)

(2)

(3)

(4)

(5)

(6)

(13)

(14)

(15)

(16)

(17)

(18)

Law

sEnvironmen

tgen

eral

Air

and

atm

osp

her

eCou

ntries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(N

O2p

c)1ststag

eln(N

O2p

c)1ststag

eln(N

O2p

c)1ststag

eln(N

O2p

c)1ststag

eln(N

O2p

c)1ststag

eln(N

O2p

c)1ststag

e

Ln(G

DPpc)?

0.50

84.05

03.64

81.03

1-0.773

-0.640

(0.483

)(2.901

)(12.63

)(1.328

)(4.157

)(2.562

)Ln(G

DPpc)

2?

0.03

980.44

00.22

50.05

16-0.095

5-0.038

2(0.037

0)(0.316

)(0.751

)(0.058

3)(0.478

)(0.174

)Open

ness

0.32

04.69

9-2.698

5.10

29.63

02.49

2(3.019

)(3.951

)(18.13

)(8.831

)(14.43

)(2.654

)Ln(P

OP)

-0.222

1.05

1-8.056

4.06

3-2.021

4.37

9(4.060

)(1.369

)(42.05

)(6.295

)(4.119

)(5.843

)Enforcem

ent(G

over

.E↵ec

t.)

-0.006

250.01

160.01

43-0.004

100.03

62-0.017

5(0.007

97)

(0.013

0)(0.103

)(0.008

95)

(0.064

6)(0.018

4)Environmen

talLaw

s?-0.018

80.01

59-0.115

0.09

290.05

640.16

4(0.049

6)(0.012

1)(0.525

)(0.209

)(0.081

0)(0.297

)Rule

ofLaw

-0.103

-0.579

-0.031

60.02

96-0.164

0.02

82(0.133

)(0.390

)(0.134

)(0.060

8)(0.258

)(0.047

9)

Observations

666

208

458

668

208

460

R-squ

ared

-0.443

-1.931

-14.47

5-3.388

-11.08

2-2.239

Number

ofis

116

3185

116

3185

Cou

ntry

sector

andtimedummies

YES

YES

YES

YES

YES

YES

Variable

F(1

,540)

P-val

F(1

,167)

P-val

F(1,

363)

P-val

F(1,

542)

P-val

F(1,

167)

P-val

F(1,

365)

P-val

Environmen

talLaw

s0.60

0.43

842.20

0.13

980.06

0.81

400.24

0.62

700.40

0.52

600.35

0.55

66Endogen

eity

test

ofen

dogen

ousre

gre

ssors:

0.18

73.32

80.55

80.45

83.17

20.95

7Chi-sq

(1)P-val=

0.66

550.06

810.45

510.49

850.07

490.32

78

Table13:LegislationonNO2IV

Environmen

tallaws

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.

Intheis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Air

and

Atm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

eforEnv

iron

mental

Law

s

SO2EM

ISSIO

NS

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

Law

sEnvironmen

tgen

eral

Ener

gy

Air

and

atm

osp

her

eCou

ntries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(SO2p

m)

1ststage

ln(SO2p

m)

1ststage

ln(SO2p

m)

1ststage

ln(SO2p

m)

1ststage

ln(SO2p

m)

1ststage

ln(SO2p

m)

1ststage

ln(SO2p

m)

1ststage

ln(SO2p

m)

1ststage

ln(SO2p

m)

1ststage

Ln(G

DPpc)?

0.101

-0.0634

0.0476

0.0875

-0.145

0.0373

0.0299

-0.0702

0.0628

(0.148)

(0.0826)

(0.225)

(0.125)

(0.448)

(0.195)

(0.292)

(0.132)

(0.141)

Ln(G

DPpc)

2?

-0.00521

-0.0113

0.00398

-0.00363

-0.0285

0.00296

-0.00308

-0.0127

-0.00560

(0.0164)

(0.0137)

(0.0451)

(0.0209)

(0.0892)

(0.0210)

(0.0237)

(0.0172)

(0.0427)

Openness

1.316

0.545

0.780

1.352

-2.433

0.707

0.275

-1.080

0.392

(2.390)

(1.418)

(1.952)

(1.877)

(14.68)

(0.766)

(3.558)

(5.595)

(2.031)

Ln(P

OP)

1.603

-0.733

1.848

1.327

1.824

1.546

0.699

-0.136

0.245

(3.211)

(0.828)

(6.285)

(1.319)

(11.27)

(2.097)

(1.766)

(1.509)

(7.881)

Enforcem

ent(G

over

.E↵ec

t.)

-0.00453

0.0102**

-0.00701

-0.00455

-0.0120

-0.00723

-0.00455

0.00190

-0.00371

(0.00636)

(0.00438)

(0.0141)

(0.00593)

(0.107)

(0.0102)

(0.00635)

(0.0253)

(0.0158)

Environmen

talLaw

s?0.00578

-0.00238

0.00691

0.0160

-0.0302

0.0110

-0.0169

-0.0143

-0.0454

(0.0357)

(0.00370)

(0.0672)

(0.0786)

(0.123)

(0.0597)

(0.0808)

(0.0335)

(0.383)

Rule

ofLaw

-0.106

-0.929**

-0.0630

-0.0660

-0.0733

-0.0845

0.0489

-0.155

0.0130

(0.140)

(0.410)

(0.141)

(0.221)

(0.294)

(0.249)

(0.0608)

(0.258)

(0.0477)

Observations

669

208

461

668

208

460

669

208

461

R-squ

ared

-0.044

0.423

-0.025

-0.563

-1.377

-0.218

-0.003

-0.085

-0.143

Number

ofis

116

3185

116

3185

116

3185

Cou

ntry

sector

andtimedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Variable

F(1,

543)

P-val

F(1,

167)

P-val

F(1,

366)

P-val

F(1,

542)

P-val

F(1,

167)

P-val

F(1,

365)

P-val

F(1,

543)

P-val

F(1,

167)

P-val

F(1,

366)

P-val

Environmen

talLaw

s0.58

0.4482

5.13

0.0248

0.20

0.6556

0.09

0.7654

0.06

0.8031

0.12

0.7340

0.65

0.4223

0.36

0.5484

0.07

0.7858

Endogen

eity

test

ofen

dogen

ousre

gre

ssors:

0.045

0.068

0.013

0.089

0.323

0.053

0.028

0.343

0.017

Chi-sq

(1)P-val=

0.8329

0.7949

0.9076

0.7658

0.5699

0.8183

0.8662

0.5582

0.8957

Table14:LegislationonSO2IV

Environmen

tallaws

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.

Intheis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Air

and

Atm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

eforEnv

iron

mental

Law

s

PM

2.5

EM

ISSIO

NS

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

Law

sEnvironmen

tgen

eral

Ener

gy

Air

and

atm

osp

her

eCou

ntries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(P

Mpc)

1ststage

ln(P

Mpc)

1ststage

ln(P

Mpc)

1ststage

ln(P

Mpc)

1ststage

ln(P

Mpc)

1ststage

ln(P

Mpc)

1ststage

ln(P

Mpc)

1ststage

ln(P

Mpc)

1ststage

ln(P

Mpc)

1ststage

Ln(G

DPpc)?

0.297

-0.0105

0.157

0.0290

-0.0237

0.00776

-0.0753

-0.0478

0.0122

(5.772)

(0.0404)

(0.924)

(0.0323)

(0.0806)

(0.0361)

(0.143)

(0.123)

(0.0498)

Ln(G

DPpc)

2?

0.170

-0.00284

0.0352

-0.00243

-0.00183

0.00228

0.0196

-0.000894

0.00911

(3.603)

(0.00462)

(0.209)

(0.00810)

(0.00697)

(0.00659)

(0.0404)

(0.00840)

(0.0207)

Openness

-4.364

-1.841**

0.178

0.0964

-1.717

0.0805

-0.732

-1.718

-0.161

(87.78)

(0.786)

(1.993)

(0.469)

(1.108)

(0.520)

(1.309)

(1.107)

(0.445)

Ln(P

OP)

-13.52

-0.824***

-4.313

-0.978*

-0.256

-1.184*

-1.495

-0.693*

-1.501

(260.0)

(0.225)

(19.09)

(0.581)

(1.143)

(0.658)

(1.234)

(0.356)

(1.251)

Enforcem

ent(G

over

.E↵ec

t.)

0.0278

0.00358

0.0111

0.00258

-0.00387

0.00284

0.00110

-0.000794

0.00331

(0.544)

(0.00355)

(0.0582)

(0.00326)

(0.0181)

(0.00384)

(0.00221)

(0.0109)

(0.00479)

Environmen

talLaw

s?-0.144

-0.00178

-0.0370

-0.00567

-0.00426

-0.00512

-0.0252

-0.00473

-0.0323

(2.917)

(0.00172)

(0.205)

(0.0101)

(0.00686)

(0.00845)

(0.0365)

(0.00658)

(0.0565)

Rule

ofLaw

0.0159

-1.381

0.0658

0.392

-0.576

0.466

0.0924

-0.519

0.0758

(0.327)

(0.930)

(0.364)

(0.576)

(0.949)

(0.638)

(0.120)

(0.634)

(0.114)

Observations

362

120

242

360

120

240

366

120

246

R-squ

ared

-1,023.552

0.793

-75.856

-1.642

0.440

-2.005

-5.865

0.517

-2.757

Number

ofis

107

3176

106

3175

109

3178

Cou

ntry

sector

andtimedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Variable

F(1,

247)

P-val

F(1,

81)

P-val

F(1,

158)

P-val

F(1,

246)

P-val

F(1,

81)

P-val

F(1,

157)

P-val

F(1,

249)

P-val

F(1,

81)

P-val

F(1,

160)

P-val

Environmen

talLaw

s0.00

0.9612

2.20

0.1415

0.03

0.8568

0.46

0.4960

0.37

0.5458

0.53

0.4668

0.59

0.4420

0.67

0.4154

0.44

0.5073

Endogen

eity

test

ofen

dogen

ousre

gre

ssors:

1.952

0.715

2.356

2.196

1.127

2.833

1.995

0.978

2.911

Chi-sq

(1)P-val=

0.1624

0.3978

0.1248

0.1384

0.2884

0.0923

0.1579

0.3227

0.0880

Table15:LegislationonPM2.5

IVEnvironmen

tallaws

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.

Intheis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Air

and

Atm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

eforEnv

iron

mental

Law

s

WATER

POLLUTIO

N

(7)

(8)

(9)

(10)

(11)

(12)

Law

sW

ater

Cou

ntries

all

OECD

NON-O

ECD

VARIA

BLES

ln(W

at.poll.pc)

1ststag

eln(W

at.poll.pc)

1ststag

eln(W

at.poll.pc)

1ststag

e

Ln(G

DPpc)?

0.02

88-0.051

50.35

6(0.073

3)(0.146

)(0.458

)Ln(G

DPpc)

2?

0.00

699

-0.047

50.00

628

(0.011

3)(0.063

5)(0.021

1)Open

ness

1.32

64.88

60.81

5(1.224

)(8.356

)(1.531

)Ln(P

OP)

-0.994

*0.25

9-2.532

(0.579

)(4.035

)(2.372

)Enforcem

ent(G

over

.E↵ec

t.)

0.00

0250

0.00

593

0.01

78(0.002

66)

(0.022

4)(0.023

0)Environmen

talLaw

s?-0.006

830.01

48-0.030

5(0.007

44)

(0.034

5)(0.037

4)Rule

ofLaw

-0.318

*-0.201

-0.114

(0.187

)(0.499

)(0.129

)

Observations

242

119

123

R-squ

ared

-0.401

-1.683

-6.342

Number

ofis

5526

29Cou

ntry

sector

andtimedummies

YES

YES

YES

Variable

F(1,

176)

P-val

F(1,

82)

P-val

F(1,

83)

P-val

Environmen

talLaw

s2.90

0.09

040.16

0.68

880.78

0.37

82Endogen

eity

test

ofen

dogen

ousre

gre

ssors:

1.71

50.30

92.24

8Chi-sq

(1)P-val=

0.19

030.30

90.13

37

Table16:LegislationonWaterIV

Environmentallaws

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.

Intheis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Air

and

Atm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

eforEnv

iron

mental

Law

s

34

FOREST

AREA

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

(15)

(16)

(17)

(18)

Law

sEnvironmen

tgen

eral

Fore

stry

Land

and

soil

Cou

ntries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(Forestpc)

1ststag

eln(Forestpc)

1ststag

eln(Forestpc)

1ststag

eln(Forestpc)

1ststag

eln(Forestpc)

1ststag

eln(Forestpc)

1ststag

eln(Forestpc)

1ststag

eln(Forestpc)

1ststag

eln(Forestpc)

1ststag

e

Ln(G

DPpc)?

0.02

450.40

90.03

820.02

400.02

070.03

700.02

28-0.015

50.03

76(0.022

4)(5.247

)(0.026

0)(0.023

0)(0.059

8)(0.025

6)(0.021

3)(0.027

7)(0.026

0)Ln(G

DPpc)

2?

0.00

0674

0.03

44-0.002

090.00

0279

0.00

0938

-0.002

310.00

0821

0.00

221

-0.002

22(0.001

72)

(0.404

)(0.002

16)

(0.001

50)

(0.002

43)

(0.002

11)

(0.002

18)

(0.002

60)

(0.002

18)

Open

ness

-0.225

*-0.316

-0.188

*-0.219

*-0.124

-0.186

*-0.214

*-0.174

-0.173

*(0.123

)(1.933

)(0.100

)(0.115

)(0.259

)(0.099

4)(0.113

)(0.208

)(0.089

8)Ln(P

OP)

-1.286

***

0.89

8-1.308

***

-1.285

***

-1.005

***

-1.305

***

-1.282

***

-0.940

***

-1.297

***

(0.155

)(24.38

)(0.182

)(0.161

)(0.155

)(0.185

)(0.148

)(0.200

)(0.171

)Enforcem

ent(G

over

.E↵ec

t.)

0.00

0624

0.00

299

0.00

0587

0.00

0589

-0.000

153

0.00

0539

0.00

0624

-0.000

718

0.00

0552

(0.000

562)

(0.042

5)(0.000

563)

(0.000

496)

(0.000

626)

(0.000

523)

(0.000

579)

(0.000

728)

(0.000

548)

Environmen

talLaw

s?-0.000

188

-0.010

8-0.000

379

-0.000

205

-0.001

17-0.000

386

-0.000

268

-0.000

278

-0.000

409

(0.000

680)

(0.131

)(0.000

705)

(0.000

790)

(0.001

42)

(0.000

753)

(0.000

996)

(0.000

361)

(0.000

796)

Rule

ofLaw

0.85

0**

-0.038

90.97

3**

0.72

8*-0.359

0.91

2*0.59

6-1.510

0.88

8*(0.347

)(0.507

)(0.406

)(0.435

)(0.262

)(0.510

)(0.395

)(0.945

)(0.455

)

Observations

651

210

441

647

210

437

644

210

434

R-squ

ared

0.66

1-54.32

40.66

60.66

00.60

00.65

90.64

50.62

10.64

9Number

ofis

113

3182

112

3181

112

3181

Cou

ntry

sector

andtimedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Variable

F(1,

526)

P-val

F(1,167)

P-val

F(1,347)

P-val

F(1,523)

P-val

F(1,167)

P-val

F(1,344)

P-val

F(1,520)

P-val

F(1,167)

P-val

F(1,341)

P-val

Environmen

talLaw

s6.00

0.01

460.01

0.93

915.73

0.01

722.80

0.09

511.89

0.17

143.20

0.07

472.28

0.13

172.55

0.11

213.82

0.05

15Endogen

eity

test

ofen

dogen

ousre

gre

ssors:

0.06

90.57

60.23

70.03

10.46

20.22

50.13

10.46

50.50

7Chi-sq

(1)P-val=

0.79

260.44

790.62

660.85

940.49

670.63

500.71

780.49

510.47

63

Table17:LegislationonForest

IVEnvironmentallaws

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.

Intheis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Air

and

Atm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

eforEnv

iron

mental

Law

s

8 Robustness

8.1 NO2 emissions

As a robustness test we performed regressions excluding the Federalist countries due totheir government setting passing law at a state level.

In addition, we performed estimations with the target variables lagged one period. Finallywe use Food and nutrition laws as an instrument.19

For NO2 emission in Table 26, we can notice that laws on Environmental general issues,Energy and Air and Atmosphere have an e↵ect decreasing pollution. For a change in oneunit, there is a decrease respectively of 0.8% (column (3)), 0.16% (column (7)) and 0.41%(column (9)).

In estimations using Food and nutrition laws as an instrument to correct the environmentallaws endogeneity, we find significant e↵ects only for determinants of pollution. Opennessand Ln(POP ) both increase NO2 emissions. These e↵ects are limited to Non-OECDcountries.

8.2 SO2 emissions

When studying the e↵ect of excluding Federalist countries, Table 35 shows Environmentallaws having an e↵ect decreasing SO2 emissions. This holds for OECD countries, in which,for a change in one unit of Environmental general issues law, there is a reduction of SO2emissions by 2.02% (Column (2)). Air and atmosphere also has the biggest impact reducingemissions of SO2 by 3.15% (Column (8)) and by 4.3% (Column (9)) for OECD and Non-OECD countries respectively.

Table 27 presents the e↵ect of lags in the variables of interest. We observe that for OECDcountries Environmental general issues and Energy laws have a decrease in SO2 emissionsby 2,75% and by 4,02% respectively. Air and atmosphere have the biggest e↵ect. Fora change in one unit of these laws there is a decrease in SO2 of 3,99% for OECD andof 4,32% for Non-OECD countries. We also observe here the decreasing e↵ect of incomewith Ln(GDP 2), but only for OECD countries. Using Food and nutrition laws as aninstrument, we find an e↵ect of population increasing SO2 emissions, but for Non-OECD

19Only summary results of these estimations are in the paper, full results tables are available from theauthors upon request

36

countries only. In this specification, we also find that instrument of the Laws on Food andnutrition performs well. Nevertheless, the laws have non significant e↵ects.

8.3 PM2.5 emissions

In Table 23, when doing the estimation without the Federalists countries, we find thatfor Non-OECD countries there are significant e↵ects of the Enforcement and the environ-mental laws, however, this e↵ect is not as expected because it appears to increase PMemissions, yet the interaction between enforcement and the laws decreases pollution, thise↵ect persists only for Non-OECD countries (in about 0,0570% to 3,01% Column (3) andColumn (7) respectively). This specifically for Non-OECD countries and in Environmentalgeneral issues and Air and atmosphere laws. For the determinants of pollution, there isa global e↵ect decreasing pollution of the Ln(GDP 2) income, but this e↵ect disappearswhen separating OECD from Non-OECD countries. As for estimations in Table 10 thee↵ect of Ln(POP ) increases pollution.

Analysing the lagged variable of environmental regulation in Table 28, there is an e↵ectof the enforcement variable. But it does not reduce PM2.5 emissions as expected, butit increases it instead. This is particularly true for Non-OECD countries. However, theinteraction of the two decreases PM2.5 emissions by 0,0238% (see Column (4)) but this isonly confirmed for all countries with Energy laws. There is a decreasing e↵ect on emissionsdue to income Ln(GDP 2) confirmed only for Non-OECD countries. For OECD countrieson the other hand, there is a decreasing e↵ect, but it is due to population.

When using Food and nutrition as an instrument for the environmental laws, we findopenness to decrease PM2.5 emissions for OECD countries and also population to have adecreasing e↵ect in both groups of countries.

8.4 Water emissions

Table 24 shows the e↵ect of the lagged variables of enforcement and environmental lawsexcluding the Federalist countries. There is an increasing e↵ect on pollution of the Wasteand hazardous substances laws. This e↵ect is suspected to be due to the same reason asin Table 11. Openness appears to have an e↵ect increasing pollution, yet this e↵ect doesnot hold when separating OECD and Non-OECD countries.

Using form of enforcement and the environmental laws Table 29, we find the same resultsas in previous specifications of the model.

37

When using the Food and nutrition laws as an instrument we find a persistent e↵ect ofopenness increasing water pollution that holds for Non-OECD countries. There is an e↵ectfor OECD of income decreasing water pollution and for Non-OECD an e↵ect of populationdecreasing Water pollution.

8.5 Forest emissions

Studying the e↵ect of excluding Federalist countries on Forest area Table 25, we findsignificant results for the environmental Laws and their enforcement. However, the e↵ectis not as expected, since it appears to have a decreasing e↵ect on forest area. Yet, theinteraction term is significant, due to the significance of the two variables, environmentalLaws and their enforcement. The interaction shows that the combined e↵ect of the lawsand their enforcement increases Forest area, but this holds only for Non-OECD countries.Environmental general issues and Forestry laws, increase Forest area by 0,0459% (Column(3)) and 0,0928% (Column (6)) respectively. There is an e↵ect of population increasingForest area only valid for OECD countries and an e↵ect of Ln(GDP 2) holds for Non-OECDcountries, decreasing forest area.

In specification of the model with the lagged form of the environmental laws and theirenforcement (Table 30), we find a persistent e↵ect of population decreasing Forest area inNon-OECD countries.

Finally using Food and nutrition Laws as an instrument, the instrument performs wellfor OECD countries for Land and Soil laws, that appear to increase Forest area, yet thee↵ect of the laws is not significant. There is an e↵ect concerning population for OECDand Non-OECD decreasing Forest area and also openness appears to decrease Forest areaconsistently.

9 Conclusions

Environmental laws intensity appear to have an e↵ect improving environmental outcomes.This e↵ect is particular to the environmental outcome and the law.

The enforcement proxy variable used in this work appears to reduce pollution only incertain outcomes, yet it is less important to decrease pollution than the laws in our model.Nevertheless, it works particularly e�ciently for Forest area, this result is particularlyinteresting for policy recommendations. There is also an e↵ect on the Laws and theirenforcement on decreasing PM 2.5 emissions.

38

The sign of the variables concerning the environmental laws, their enforcement, and theinteraction between both is not always what is expected. Nevertheless, analysing resultsthat are significant and robust to the group of countries, we notice that they follow the logicintuition of the model. Yet, we think our model could fail to capture more institutionalnuances. We think there is a fertile ground for research to overcome this drawback in ourmodel.

The expected e↵ects of the corresponding laws with outcomes are confirmed, validatingthe intuition behind our underlying model.

Air and Atmosphere seem to have the biggest e↵ect on local air pollutants. Also Environ-mental general issues improve Air pollution and increase Forest area.

The e↵ect of the environmental regulation proxied with environmental laws is reinforcedwhen excluding the Federalist countries. This is specially true for PM2.5 and Forestarea.

Additionally, the Environmental Laws have a slightly better explanatory e↵ect on theoutcomes, particularly concerning the local air pollutants.

The significant e↵ects of the laws are more frequent for Non-OECD countries. This suggestsa policy recommendation towards investing in reinforcing institutions. More specifically,stressing the specific law creation in developing countries might be a crucial e↵ort in orderto protect the environment and to fight against climate change.

The e↵ect of trade improving environmental outcomes, openness e↵ect, is only partiallyconfirmed. It has a decreasing e↵ect only for OECD countries in PM2.5 emissions andan increasing e↵ect for Non-OECD countries in NO2 emissions. In addition, opennessincreases water pollution for Non-OECD. Forest area in particular challenges the resultsof Frankel and Rose (2005), openness consistently showing a decrease in forest area. Withour results, we believe the e↵ect of trade on the environment is not straightforward.

Only the squared form of income presents significant e↵ects, this e↵ect being mostly neg-ative confirming the concave form of the income e↵ect that increases pollution but withdecreasing e↵ects. Yet, these e↵ects are more common globally than for specific developingor developed countries.

The e↵ect of population is to increase PM2.5 emissions for Non-OECD countries. Thise↵ect is not driven for emerging countries. For OECD countries there is an increasinge↵ect with population, which can be part of the forest transition and the EKC.

39

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Appendix

43

Trade first stage

(1)VARIABLES ln(NOX emissions)

Ln(POP) importer -0.0229***(0.00708)

Ln(POP) exporter 0.748***(0.00673)

Ln(distance) -1.269***(0.0213)

AREA 0***(0)

COMLANG 0.617***(0.0410)

CONTIG 0.984***(0.0883)

LANDLOK -0.994***(0.0291)

Ln(landcap) 0.0701***(0.00697)

REMOTE 0.00478(0.00323)

Constant -3.045***(0.236)

Observations 410,306R-squared 0.355Country dummies NOTime dummies NOCountry-time dummies NOBilateral dummies NO

Table 18: First stage IV trade and geographic variables

44

Income first stage

(1)VARIABLES ln(GDPpc)

Ln(POP) -0.0307***(0.0103)

Ln(GDPpc)t-1 2.679*(1.621)

Ln(I/GDP) 0.0287(0.0544)

Growth pop. 6.988***(2.199)

Ln(school1) -1.763***(0.0976)

Ln(school2) 2.215***(0.0500)

Constant -6.387***(0.388)

Observations 2,579R-squared 0.582Country-time dummies NO

Table 19: First stage IV income and growth variables

45

List of variables by source

NO2 Emission database for global atmospheric research (EDGAR)SO2 Emission database for global atmospheric research (EDGAR)PM2.5 Emission database for global atmospheric research (EDGAR)

Water pollution World Bank Development Index (WDI)Forest area World Bank Development Index (WDI)

Population World Bank Development Index (WDI)Investment World Bank Development Index (WDI)Schooling World Bank Development Index (WDI)Population World Bank Development Index (WDI)Population growth rate World Bank Development Index (WDI)GDP World Bank Development Index (WDI)

Trade (Imports and exports) Centre d’Etudes Prospectives et d’informations Internationales (CEPII)Geografical variables (gravity variables) Centre d’Etudes Prospectives et d’informations Internationales (CEPII)

Environmental Laws ECOLEX The gateway to environmental law

Goverment E↵ectiveness The Worldwide Governance Indicators (WGI) projectRule of Law The Worldwide Governance Indicators (WGI) project

Table 20: Sources of the data

46

NO2EM

ISSIO

NS

WIT

HOUT

FEDERALIS

TCOUNTIR

ES

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

LAW

SEnvironmen

tgen

.Ener

gy

Air

and

atm

os.

Countries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)

Ln(G

DPpc)?

0.78

02.27

11.00

20.73

12.35

10.97

50.77

12.15

61.03

0(0.872

)(3.072

)(1.018

)(0.899

)(2.988

)(1.089

)(0.889

)(3.246

)(1.099

)Ln(G

DPpc2)?

0.05

140.26

10.06

470.04

760.26

80.06

180.05

130.24

90.06

62(0.074

6)(0.328

)(0.082

8)(0.078

1)(0.321

)(0.087

3)(0.076

4)(0.347

)(0.087

9)Open

ness

1.30

30.56

31.02

11.23

90.53

71.09

50.84

80.55

80.55

0(1.003

)(2.052

)(1.358

)(1.224

)(1.965

)(2.279

)(1.029

)(1.930

)(1.665

)Ln(P

OP)

0.80

51.33

20.52

10.83

21.31

30.62

70.95

01.33

60.90

0(0.924

)(1.422

)(1.042

)(0.861

)(1.740

)(1.089

)(0.866

)(1.482

)(1.093

)Enforcem

ent(G

over

.E↵ec

t.)

-0.009

82-0.002

88-0.011

3-0.008

96-0.004

33-0.010

6-0.008

51-0.001

59-0.010

6(0.006

62)

(0.009

91)

(0.007

92)

(0.006

47)

(0.008

75)

(0.007

64)

(0.006

54)

(0.008

77)

(0.007

46)

Environmen

talLaw

s-0.007

83-0.000

199

-0.013

30.00

0329

-0.004

03-0.004

04-0.006

740.00

230

-0.037

8(0.005

72)

(0.011

2)(0.008

60)

(0.003

16)

(0.017

9)(0.006

09)

(0.009

67)

(0.016

7)(0.028

6)Enforcem

entxLaw

s7.79

e-05

5.71

e-06

0.00

0166

3.25

e-06

4.31

e-05

9.16

e-05

6.82

e-05

-1.80e-05

0.00

0693

(6.42e-05)

(0.000

120)

(0.000

120)

(5.38e-05)

(0.000

187)

(0.000

118)

(0.000

110)

(0.000

183)

(0.000

491)

Observations

574

162

412

576

162

414

575

162

413

R-squ

ared

0.08

20.23

40.09

70.06

70.23

50.07

30.06

80.23

50.08

3Number

ofis

107

2483

108

2484

108

2484

Countrysectorand

timedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Bootstrapped

standard

erro

rsYES

YES

YES

YES

YES

YES

YES

YES

YES

Table21:NO2em

issionswithoutfederalist

countries

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.In

theis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Airan

dAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

e.

SO2EM

ISSIO

NS

WIT

HOUT

FEDERALIS

TCOUNTRIE

S

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

LAW

SEnvironmen

tgen

.Ener

gy

Air

and

atm

os.

Countries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)

Ln(G

DPpc)?

0.16

7-0.041

00.15

00.15

2-0.063

60.14

10.17

9-0.020

80.17

2(0.174

)(0.174

)(0.202

)(0.181

)(0.164

)(0.205

)(0.171

)(0.164

)(0.203

)Ln(G

DPpc2)?

-0.004

06-0.044

80.00

794

-0.002

41-0.041

40.00

754

-0.000

239

-0.038

10.00

931

(0.010

5)(0.034

0)(0.013

0)(0.011

0)(0.032

9)(0.013

3)(0.010

3)(0.030

9)(0.014

2)Open

ness

0.85

30.65

90.57

30.77

00.87

60.56

70.77

90.80

50.46

8(1.208

)(1.881

)(1.303

)(1.165

)(1.855

)(1.295

)(1.106

)(2.058

)(1.223

)Ln(P

OP)

0.81

60.19

10.68

81.00

10.99

10.91

50.68

40.27

70.77

4(0.778

)(1.695

)(1.001

)(0.795

)(1.995

)(0.999

)(0.792

)(1.650

)(1.035

)Enforcem

ent(G

over

.E↵ec

t.)

-0.007

24-0.002

78-0.009

32-0.005

400.00

250

-0.008

49-0.007

20-0.000

304

-0.009

61(0.006

40)

(0.009

51)

(0.007

08)

(0.006

25)

(0.008

38)

(0.007

10)

(0.005

92)

(0.008

30)

(0.006

37)

Environmen

talLaw

s-0.00891*

-0.0202**

-0.010

7-0.000

269

-0.028

8-0.005

34-0.0256**

-0.0315*

-0.0430*

(0.004

86)

(0.009

78)

(0.008

35)

(0.003

07)

(0.020

5)(0.005

27)

(0.010

3)(0.017

4)(0.025

6)Enforcem

entxLaw

s8.05

e-05

0.000227**

0.00

0123

-1.28e-05

0.00

0328

9.29

e-05

0.000260**

0.000355*

0.00

0692

(5.98e-05)

(0.000

109)

(0.000

127)

(5.21e-05)

(0.000

226)

(0.000

115)

(0.000

119)

(0.000

193)

(0.000

475)

Observations

572

162

410

574

162

412

575

162

413

R-squ

ared

0.09

80.52

50.09

40.08

10.50

50.08

00.09

80.51

80.09

0Number

ofis

107

2483

107

2483

108

2484

Countrysectorand

timedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Bootstrapped

standard

erro

rsYES

YES

YES

YES

YES

YES

YES

YES

YES

Table22:SO2em

issionswithoutfederalist

countries

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.In

theis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Airan

dAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

e.

PM

2.5

EM

ISSIO

NS

WIT

HOUT

FEDERALIS

TCOUNTRIE

S

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

LAW

SEnvironmen

tgen

.Ener

gy

Air

and

atm

os.

Countries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(P

Mpc)

ln(P

Mpc)

ln(P

Mpc)

ln(P

Mpc)

ln(P

Mpc)

ln(P

Mpc)

ln(P

Mpc)

ln(P

Mpc)

ln(P

Mpc)

Ln(G

DPpc)

-0.036

3-0.016

6-0.044

5-0.020

4-0.028

7-0.027

2-0.026

8-0.031

2-0.042

1(0.025

3)(0.065

6)(0.029

4)(0.028

5)(0.065

5)(0.031

6)(0.028

6)(0.067

7)(0.034

3)Ln(G

DPpc2)

-0.002

91**

-0.004

48-0.000

737

-0.003

67**

*-0.007

00-0.001

33-0.004

18**

*-0.004

97-0.001

87(0.001

39)

(0.005

78)

(0.001

75)

(0.001

39)

(0.005

61)

(0.001

77)

(0.001

32)

(0.005

78)

(0.001

73)

Open

ness

0.09

77-0.640

0.10

60.00

448

-0.488

-0.033

70.09

52-0.322

0.13

2(0.200

)(0.917

)(0.416

)(0.191

)(0.941

)(0.419

)(0.201

)(0.940

)(0.309

)Ln(P

OP)

0.63

9***

0.76

6***

0.61

0***

0.73

0***

0.58

5***

0.76

8***

(0.123

)(0.175

)(0.129

)(0.171

)(0.126

)(0.151

)Enforcem

ent(G

over

.E↵ec

t.)

0.00264**

0.00

629*

0.00228**

0.00223**

0.00

419

0.00

186

0.00211**

0.00621*

0.00184*

(0.001

03)

(0.003

50)

(0.001

14)

(0.001

06)

(0.003

04)

(0.001

16)

(0.000

992)

(0.003

26)

(0.001

04)

Environmen

talLaw

s0.00336***

-0.000

437

0.00378**

0.00290***

-0.002

760.00

267

0.00788**

-0.000

120

0.0193***

(0.001

12)

(0.002

37)

(0.001

49)

(0.001

11)

(0.003

72)

(0.001

86)

(0.003

80)

(0.003

55)

(0.006

05)

Enforcem

entxLaw

s-4.85e-05***

-1.73e-06

-5.70e-05**

-4.52e-05***

2.32

e-05

-4.21e-05

-0.000104**

-6.70e-06

-0.000301***

(1.44e-05)

(2.66e-05)

(2.70e-05)

(1.58e-05)

(4.40e-05)

(3.28e-05)

(4.80e-05)

(3.97e-05)

(0.000

103)

Observations

317

9222

531

492

222

317

9222

5R-squ

ared

0.71

10.87

70.68

10.71

10.87

80.67

70.70

50.87

70.70

6Number

ofis

105

2481

102

2478

105

2481

Countrysectorand

timedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Bootstrapped

standard

erro

rsYES

YES

YES

YES

YES

YES

YES

YES

YES

Table23:PM2.5

emissionswithoutfederalist

countries

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.In

theis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Airan

dAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

e.

WATER

POLLUTIO

NW

ITHOUT

FEDERALIS

TCOUNTRIE

S

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

LAW

SEnvironmen

tgen

.W

ater

Wasteand

haza

rdoussu

bstance

sCountries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

Ln(G

DPpc)

0.03

800.01

04-0.030

80.03

150.00

126

-0.054

60.03

660.00

630

-0.023

8(0.077

3)(0.109

)(0.131

)(0.076

2)(0.118

)(0.116

)(0.077

7)(0.110

)(0.136

)Ln(G

DPpc2)

-0.000

377

-0.017

50.00

672

-0.003

18-0.022

50.00

362

-0.001

27-0.015

60.00

632

(0.009

07)

(0.015

5)(0.014

3)(0.008

81)

(0.015

3)(0.012

6)(0.008

60)

(0.016

0)(0.012

4)Open

ness

2.94

1**

2.31

72.29

43.03

6**

2.15

12.43

32.70

3***

2.73

12.06

7(1.153

)(3.499

)(1.735

)(1.201

)(3.324

)(1.691

)(0.984

)(3.169

)(1.275

)Ln(P

OP)

-0.997

-0.959

-0.677

-1.037

-1.038

-0.556

-0.914

-0.978

-0.617

(0.740

)(1.806

)(0.974

)(0.728

)(1.941

)(0.889

)(0.709

)(2.023

)(0.903

)Enforcem

ent(G

over

.E↵ec

t.)

-0.000

251

0.00

132

-0.001

03-0.000

443

-0.000

838

-0.003

390.00

0943

0.00

206

-0.000

647

(0.002

44)

(0.007

89)

(0.003

64)

(0.002

49)

(0.007

62)

(0.003

92)

(0.002

34)

(0.006

87)

(0.003

20)

Environmen

talLaw

s0.00

256

0.00

746

0.00

139

0.00

250

0.00

312

0.00

0827

0.00715**

0.00

744

0.00

681

(0.002

02)

(0.009

65)

(0.003

36)

(0.003

27)

(0.007

83)

(0.005

97)

(0.003

06)

(0.006

45)

(0.009

18)

Enforcem

entxLaw

s-2.55e-05

-8.30e-05

-1.11e-05

-1.29e-05

-2.07e-05

4.19

e-05

-7.68e-05**

-7.64e-05

-7.94e-05

(2.64e-05)

(0.000

112)

(7.35e-05)

(4.14e-05)

(9.60e-05)

(0.000

102)

(3.84e-05)

(7.28e-05)

(0.000

132)

Observations

214

101

113

214

101

113

216

101

115

R-squ

ared

0.28

20.45

80.22

00.28

50.45

60.24

00.29

60.48

10.21

3Number

ofis

5322

3153

2231

5322

31Countrysectorand

timedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Bootstrapped

standard

erro

rsYES

YES

YES

YES

YES

YES

YES

YES

YES

Table24:Waterpollutionwithoutfederalist

countries

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.In

theis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Airan

dAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

e.

FOREST

AREA

WIT

HOUT

FEDERALIS

TCOUNTRIE

S

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

LAW

SEnvironmen

tgen

.Fore

stry

Land

and

Soil

Countries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

Ln(G

DPpc)

0.02

27-0.019

00.03

490.02

84-0.013

80.04

240.01

44-0.008

240.02

32(0.027

4)(0.029

9)(0.030

5)(0.027

1)(0.028

8)(0.026

7)(0.025

4)(0.027

7)(0.028

1)Ln(G

DPpc2)

-0.002

57-0.000

231

-0.005

16*

-0.003

090.00

0490

-0.005

71**

-0.001

09-1.00e-05

-0.003

93(0.002

23)

(0.002

88)

(0.002

94)

(0.002

08)

(0.002

76)

(0.002

63)

(0.002

35)

(0.002

89)

(0.003

19)

Open

ness

-0.152

-0.085

6-0.133

-0.139

-0.090

4-0.104

-0.171

-0.135

-0.135

(0.320

)(0.204

)(0.521

)(0.290

)(0.258

)(0.533

)(0.336

)(0.246

)(0.557

)Ln(P

OP)

1.22

6***

0.92

0***

1.22

6***

0.95

9***

1.23

5***

0.98

0***

(0.126

)(0.131

)(0.135

)(0.141

)(0.138

)(0.140

)Enforcem

ent(G

over

.E↵ec

t.)

-0.000845*

-0.000126

-0.00164**

-0.00135**

0.00

0309

-0.00206***

-0.000

286

0.00

0143

-0.000

855

(0.000

497)

(0.001

05)

(0.000

721)

(0.000

538)

(0.001

15)

(0.000

691)

(0.000

591)

(0.001

12)

(0.000

783)

Environmen

talLaw

s-0.00151*

0.00

177

-0.00285**

-0.00437***

0.00

259

-0.00622***

0.00

0394

0.00

151

0.00

0222

(0.000

780)

(0.001

35)

(0.001

13)

(0.001

47)

(0.002

22)

(0.001

76)

(0.000

687)

(0.002

13)

(0.000

935)

Enforcem

entxLaw

s2.10e-05**

-1.71e-05

4.59e-05**

5.95e-05***

-2.81e-05

9.28e-05***

-2.20e-06

-1.62e-05

5.41

e-06

(9.97e-06)

(1.56e-05)

(1.80e-05)

(1.99e-05)

(2.49e-05)

(2.57e-05)

(8.39e-06)

(2.14e-05)

(1.55e-05)

Observations

546

161

385

547

161

386

549

161

388

R-squ

ared

0.69

10.63

30.71

20.70

30.59

50.72

80.68

30.59

50.70

1Number

ofis

104

2480

105

2481

105

2481

Countrysectorand

timedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Bootstrapped

standard

erro

rsYES

YES

YES

YES

YES

YES

YES

YES

YES

Table25:Forest

areawithoutfederalist

countries

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.In

theis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Airan

dAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

e.

NO2EM

ISSIO

NS

LAGGED

ENVIR

ONM

ENTAL

LAW

S

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

LAW

SEnvironmen

tgen

.Ener

gy

Air

and

atm

os.

Countries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)

Ln(G

DPpc)?

0.732

0.581

0.789

0.699

0.432

0.771

0.729

0.535

0.840

(0.814)

(0.981)

(1.153)

(0.830)

(1.030)

(1.164)

(0.767)

(1.042)

(1.184)

Ln(G

DPpc2)?

0.0558

0.0566

0.0616

0.0544

0.04

050.0609

0.05

640.0510

0.0650

(0.0731)

(0.109)

(0.0913)

(0.0749)

(0.114)

(0.0916)

(0.0681)

(0.115)

(0.0934)

Openness

1.234

0.252

1.053

1.221

0.31

21.084

1.224

0.280

1.075

(1.216)

(1.166)

(2.363)

(1.403)

(1.134)

(2.694)

(1.384)

(1.286)

(2.350)

Ln(P

OP)

1.134

-0.275

0.851

1.421

-0.426

1.273

1.232

-0.291

1.128

(0.982)

(0.569)

(1.098)

(0.970)

(0.618)

(1.141)

(0.929)

(0.613)

(1.104)

Enforcem

ent(G

over

.E↵ec

t.)t-1

-0.00280

0.00687*

-0.00446

-0.00158

0.00752**

-0.00345

-0.00311

0.00696*

-0.00494

(0.00447)

(0.00407)

(0.00535)

(0.00427)

(0.00365)

(0.00513)

(0.00459

)(0.00379)

(0.00592)

Environmen

talLaw

st-1

-0.00504

0.00443

-0.00844*

0.000397

0.0123

-0.00419

-0.0156*

0.00822

-0.0406**

(0.00330)

(0.00463)

(0.00494)

(0.00488)

(0.00851)

(0.00710)

(0.00864

)(0.00776)

(0.0201)

Enforcem

entxLaw

st-1

2.29e-05

-4.82e-05

7.36e-05

-4.61e-05

-0.00013

74.71e-05

0.000124

-8.56e-05

0.000601*

(3.66e-05)

(4.84e-05)

(6.98e-05)

(6.12e-05)

(8.70e-05)

(0.000138)

(9.35e-05)

(8.10e-05)

(0.000

338)

Observations

572

178

394

576

178

398

572

178

394

R-squ

ared

0.077

0.330

0.100

0.065

0.343

0.081

0.073

0.331

0.09

4Number

ofis

122

3191

122

3191

122

3191

Countrysectorand

timedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Bootstrapped

standard

erro

rsYES

YES

YES

YES

YES

YES

YES

YES

YES

Table26:NO2em

issionslagged

environmentallaws

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.In

theis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Airan

dAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

e.

SO2EM

ISSIO

NS

LAGGED

ENVIR

ONM

ENTAL

LAW

S

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

LAW

SEnvironmen

tgen

.Ener

gy

Air

and

atm

os.

Countries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)

Ln(G

DPpc)?

0.08

910.11

30.03

850.07

980.08

670.03

410.08

680.08

940.03

99(0.159

)(0.079

7)(0.182

)(0.164

)(0.081

3)(0.198

)(0.163

)(0.081

9)(0.189

)Ln(G

DPpc2)?

-0.019

2*-0.064

5**

-0.003

41-0.017

1-0.057

2*-0.002

25-0.018

2*-0.054

4*-0.003

09(0.010

6)(0.028

5)(0.014

7)(0.011

2)(0.030

6)(0.015

1)(0.010

8)(0.029

9)(0.014

7)Open

ness

0.87

21.40

20.61

70.88

51.11

80.65

10.93

41.17

60.62

3(1.329

)(2.021

)(1.928

)(1.324

)(1.922

)(1.724

)(1.367

)(1.701

)(1.168

)Ln(P

OP)

1.07

1-1.228

1.08

71.26

8*-0.464

1.29

90.97

2-1.057

1.18

0(0.731

)(0.912

)(0.856

)(0.711

)(1.109

)(0.878

)(0.702

)(0.983

)(0.899

)Enforcem

ent(G

over

.E↵ec

t.)t-1

-0.001

50-0.009

95-0.003

11-0.000

399

-0.002

32-0.002

71-0.002

48-0.005

16-0.005

00(0.003

48)

(0.007

27)

(0.004

01)

(0.003

49)

(0.007

09)

(0.004

25)

(0.003

58)

(0.006

89)

(0.004

14)

Environmen

talLaw

st-1

-0.005

35-0.0275***

-0.006

39-0.002

15-0.0402*

-0.006

66-0.0268***

-0.0399*

-0.0432**

(0.003

72)

(0.008

57)

(0.004

77)

(0.003

79)

(0.020

9)(0.005

99)

(0.008

79)

(0.020

9)(0.019

3)Enforcem

entxLaw

st-1

4.03

e-05

0.000305***

7.52

e-05

-7.50e-06

0.000446**

0.00

0104

0.000267***

0.000441*

0.000702**

(4.31e-05)

(9.40e-05)

(7.74e-05)

(5.73e-05)

(0.000

223)

(0.000

122)

(9.61e-05)

(0.000

226)

(0.000

338)

Observations

571

178

393

573

178

395

575

178

397

R-squ

ared

0.10

10.57

50.09

50.09

20.52

80.08

80.11

50.54

70.10

7Number

ofis

121

3190

123

3192

123

3192

Countrysectorand

timedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Bootstrapped

standard

erro

rsYES

YES

YES

YES

YES

YES

YES

YES

YES

Table27:SO2em

issionslagged

environmentallaws

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.In

theis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Airan

dAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

e.

PM

2.5

EM

ISSIO

NS

LAGGED

ENVIR

ONM

ENTAL

LAW

S

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

LAW

SEnvironmen

tgen

.Ener

gy

Air

and

atm

os.

Countries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(P

M2.5p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)ln(N

O2p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)ln(N

O2p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)

Ln(G

DPpc)?

0.0162

0.00283

0.00581

0.00871

-0.00881

0.000200

0.0154

-0.0223

0.00198

(0.0269)

(0.0916)

(0.0268)

(0.0249)

(0.103)

(0.0270)

(0.0278)

(0.0998)

(0.0264)

Ln(G

DPpc2)?

-0.0105***

-0.00960

-0.00639*

-0.0106***

-0.0108

-0.00779**

-0.0110***

-0.00793

-0.00676*

(0.00275)

(0.00889)

(0.00375)

(0.00256)

(0.00798)

(0.00351)

(0.00265)

(0.00949)

(0.00375)

Openness

-0.149

-1.079

-0.0874

-0.181

-1.016

-0.124

-0.152

-1.071

-0.0827

(0.215)

(0.910)

(0.637)

(0.211)

(0.983)

(0.617)

(0.232)

(0.945)

(0.708)

Ln(P

OP)

-0.838***

-1.045***

-0.775***

-0.964***

-0.783***

-1.032***

(0.144)

(0.294)

(0.132)

(0.308)

(0.135)

(0.314)

Enforcem

ent(G

over

.E↵ec

t.)t-1

0.00277**

0.00446

0.00287**

0.00263**

0.00330

0.00255*

0.00253**

0.00602*

0.00267**

(0.00123)

(0.00321)

(0.00146)

(0.00117)

(0.00324)

(0.00142)

(0.00122)

(0.00336)

(0.00132)

Environmen

talLaw

st-1

0.000384

-0.00224

0.000595

0.00153*

-0.00378

0.00192

0.00149

-0.000871

0.00469

(0.000803)

(0.00171)

(0.00146)

(0.000854)

(0.00304)

(0.00146)

(0.00239)

(0.00342)

(0.00582)

Enforcem

entxLaw

st-1

-1.11e-05

2.03e-05

-1.81e-05

-2.38e-05*

3.86e-05

-3.26e-05

-2.28e-05

6.85e-06

-8.88e-05

(1.02e-05)

(1.92e-05)

(2.63e-05)

(1.33e-05)

(3.50e-05)

(2.98e-05)

(2.73e-05)

(3.83e-05)

(0.000108)

Observations

278

90188

277

90187

278

90188

R-squ

ared

0.742

0.888

0.682

0.753

0.886

0.700

0.738

0.878

0.685

Number

ofis

114

3183

113

3182

114

3183

Countrysectorand

timedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Bootstrapped

standard

erro

rsYES

YES

YES

YES

YES

YES

YES

YES

YES

Table28:PM2.5

emissionslagged

environmentallaws

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.In

theis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Airan

dAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

e.

WATER

POLLUTIO

NLAGGED

ENVIR

ONM

ENTAL

LAW

S

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

LAW

SEnvironmen

tgen

.W

ater

Wasteand

haza

rdoussu

bstance

sCountries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

ln(W

at.poll.pc)

Ln(G

DPpc)?

0.03

190.00

122

-0.041

70.03

280.00

0816

-0.069

90.02

56-0.002

26-0.041

4(0.085

3)(0.105

)(0.143

)(0.083

2)(0.106

)(0.148

)(0.083

8)(0.106

)(0.144

)Ln(G

DPpc2)?

-0.004

13-0.033

00.00

532

-0.004

40-0.032

4*0.00

453

-0.001

05-0.028

70.00

383

(0.010

1)(0.020

3)(0.014

6)(0.009

69)

(0.016

9)(0.014

1)(0.009

06)

(0.018

5)(0.013

3)Open

ness

1.70

11.40

80.87

91.76

81.78

60.93

11.75

61.64

21.10

5(1.150

)(4.928

)(1.693

)(1.149

)(4.178

)(1.825

)(1.137

)(4.330

)(1.596

)Ln(P

OP)

-0.446

11,616

0.20

6-0.485

11,913

0.20

3-0.373

11,736

0.22

5(0.889

)(13,68

8)(0.972

)(0.844

)(11,91

2)(1.019

)(0.754

)(12,43

1)(0.955

)Enforcem

ent(G

over

.E↵ec

t.)t-1

-0.002

29-0.006

52-0.003

37-0.001

91-0.004

64-0.004

010.00

0434

-0.003

68-0.001

83(0.003

06)

(0.007

67)

(0.003

68)

(0.002

97)

(0.009

54)

(0.004

37)

(0.002

66)

(0.008

01)

(0.003

38)

Environmen

talLaw

st-1

-0.000

199

-0.003

651.22

e-05

0.00

0416

0.00

0170

3.42

e-05

0.00929*

0.00

169

0.00

819

(0.003

16)

(0.010

9)(0.004

08)

(0.003

70)

(0.009

83)

(0.005

16)

(0.004

79)

(0.008

49)

(0.008

88)

Enforcem

entxLaw

st-1

1.06

e-05

4.29

e-05

1.82

e-05

7.25

e-06

1.35

e-05

5.01

e-05

-9.97e-05*

-1.41e-05

-5.92e-05

(3.90e-05)

(0.000

125)

(7.14e-05)

(4.09e-05)

(0.000

108)

(9.52e-05)

(5.60e-05)

(9.31e-05)

(0.000

126)

Observations

198

9510

319

895

103

199

9510

4R-squ

ared

0.14

90.40

50.11

70.15

40.42

40.12

70.18

80.40

70.15

0Number

ofis

5826

3258

2632

5926

33Countrysectorand

timedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Bootstrapped

standard

erro

rsYES

YES

YES

YES

YES

YES

YES

YES

YES

Table29:Waterpollutionlagged

environmentallaws

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.In

theis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Airan

dAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

e.

FOREST

AREA

LAGGED

ENVIR

ONM

ENTAL

LAW

S

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

LAW

SEnvironmen

tgen

.Fore

stry

Land

and

soil

Countries

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

all

OECD

NON-O

ECD

VARIA

BLES

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

Ln(G

DPpc)?

0.03

56-0.007

650.04

810.03

390.00

530

0.04

790.03

29-0.002

360.04

56(0.030

1)(0.022

1)(0.034

5)(0.032

0)(0.020

7)(0.035

1)(0.030

5)(0.022

0)(0.036

8)Ln(G

DPpc2)?

0.00

0130

0.00

0703

-0.001

520.00

0467

0.00

0206

-0.001

460.00

0602

0.00

0336

-0.001

40(0.001

85)

(0.003

04)

(0.002

45)

(0.001

84)

(0.003

01)

(0.002

52)

(0.001

75)

(0.002

78)

(0.002

42)

Open

ness

-0.202

-0.207

-0.176

-0.211

-0.164

-0.175

-0.205

-0.193

-0.166

(0.288

)(0.170

)(0.520

)(0.303

)(0.170

)(0.547

)(0.275

)(0.196

)(0.524

)Ln(P

OP)

-1.251

***

-1.251

***

-1.237

***

(0.176

)(0.180

)(0.173

)Enforcem

ent(G

over

.E↵ec

t.)t-1

0.00

0628

-7.10e-05

0.00

0522

0.00

0688

0.00

0212

0.00

0494

0.00

0795

0.00

0202

0.00

0646

(0.000

577)

(0.000

869)

(0.000

725)

(0.000

637)

(0.001

05)

(0.000

792)

(0.000

634)

(0.001

07)

(0.000

824)

Environmen

talLaw

st-1

-0.000

348

0.00

0875

-0.000

405

-0.000

320

0.00

102

-0.000

512

1.21

e-05

0.00

114

-9.22e-06

(0.000

464)

(0.001

02)

(0.000

722)

(0.001

37)

(0.001

75)

(0.001

95)

(0.000

669)

(0.001

26)

(0.000

795)

Enforcem

entxLaw

st-1

6.30

e-06

-9.46e-06

8.58

e-06

5.89

e-06

-1.46e-05

1.15

e-05

9.94

e-07

-1.29e-05

2.76

e-06

(5.55e-06)

(1.17e-05)

(1.13e-05)

(1.55e-05)

(1.90e-05)

(2.80e-05)

(7.05e-06)

(1.34e-05)

(1.12e-05)

Observations

552

179

373

546

179

367

551

179

372

R-squ

ared

0.67

50.70

30.68

50.67

30.71

20.68

40.67

40.71

10.68

5Number

ofis

119

3188

117

3186

118

3187

Countrysectorand

timedummies

YES

YES

YES

YES

YES

YES

YES

YES

YES

Bootstrapped

standard

erro

rsYES

YES

YES

YES

YES

YES

YES

YES

YES

Table30:Forest

arealagged

environmen

tallaws

Note:

Rob

ust

stan

darderrors

arein

betweenbrackets.

***,

**,*den

otestatisticalsign

ificance

ata1,

5an

d10

percent

level,

respectively.In

theis

dim

ension

,irefers

tocountry,srefers

tothesubject

ofthelaw

(Airan

dAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.)?O

pen

nessan

dIncomearepredictedvalues

from

theinstrumental-variab

lefirststag

e.

Matching the environmental laws with the outcomes

In order to match the environmental outcomes with the correspondent laws, first we per-formed estimations with all the type of laws, and then we restricted the laws to thoserelated to each corresponded environmental outcome. From the environmental subjects ofour data we expect Air and atmosphere, Energy and Environmental general issues to havea decreasing e↵ect on air pollution outcomes. We performed estimations with all laws inall subjects, then combining the three subjects Air and atmosphere, Energy and Environ-mental general, then combining in groups of two these three subjects and then individually.Use this same procedure we choose the laws for the other outcomes, taking into accountthe subjects that could a↵ect those outcomes. Results are in Tables 31 to 35.

Table 31 show the results for NO2 emissions. Since these emissions are mainly a result ofroad tra�c and energy production, we expect energy and air pollution laws having a moreimportant impact on these emissions. Results show Air and atmosphere related laws havea bigger impact used individually (8) and also Air and atmosphere and Environmentalgeneral issues (4). Enforcement on the other side has the biggest impact using Energylaws (7). The combination of laws and enforcement expressed with the interaction term isconsistently positive significant and of small size, further explanation about it is developedin the section addressing simultaneity see section 8. The other determinants of pollutionresults are similar in all specifications, we develop about them in section 7.

For SO2 emissions, since they result from industrial processes, mainly coal and petroleumcombustion, we expect mainly Air and atmosphere and Environmental general laws havingan impact. The same estimations were performed using SO2 emissions. Results show, theenvironmental laws are systematically significant, the enforcement variable on the other sideis no longer significant when single laws are used. The biggest e↵ect comes from the laws inEnvironmental general issues (6), but also specifications (3) and (4) containing Energy andEnvironmental general issues and Air and atmosphere and Environmental general issues.Enforcement e↵ect is the biggest in specification only containing Air and atmosphere laws(8). The combination of laws and enforcement expressed with the interaction term hassimilar results then for NO2. For these results refer to 32.

In the case of PM 2.5 emissions are linked to burning of fossil fuels in vehicles, powerplants and various industrial processes. We expect all the three laws having an impact,specially Environmental general issues. Results are found in 33. Interestingly, this spec-ification show what environmental laws and enforcement increase pollution, nevertheless,enforcement combined with environmental law decreases pollution. However, the size ofthe environmental laws coe�cient is bigger then the interaction, and even more is thedi↵erence in size with enforcement coe�cient. Nevertheless, the enforcement variable isno longer significant when the laws are used individually. The most important e↵ect of

57

the laws is for Environmental general issues (6). Enforcement, contrarily, has its moreimportant e↵ect in (5) using Energy and Air and atmosphere laws.

We think is coherent to restrict our work in these air pollutants to these three air pollutionrelated type of laws. Air and atmosphere, Energy and Environmental general are thesubjects of laws used for emissions of NO2, SO2 and PM 2.5 in the remainder of thiswork.

For water pollution, we use Organic water pollutant that are measured by biochemicaloxygen demand (BOD), which refers to the amount of oxygen that bacteria in water willconsume in breaking down waste. Table 34 show results. In this case we use all lawsand also sub groups with laws in Water and Environmental general issues. Results arenor so significant, except for all laws together. Since water pollution is a more localisedissue, a drawback of our variable come to light, the laws used are laws passed at a nationallevel, since water pollution is mainly an issue approached at a federal level, federalism isnecessary to be considered. In section 7 we are going to discuss these results further andin section 8 we addressed this also.

In the case of Forest area, results of the variables are to be read contrarily then before.Results are no significant for the enforcement variable in the case of the laws they aresignificant when used not individually, nevertheless, they show a decrease on Forest area.The interaction, however, increases the forest area. Further discussion follow in section7.

58

NO2EM

ISSIO

NS

OLS

Leg

islation

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

VARIA

BLES

ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)ln(N

O2p

c)

Ln(G

DPpc)

-0.518

***

-0.524

***

-0.498

***

-0.548

***

-0.527

***

-0.518

*-0.478

*-0.578

**(0.065

3)(0.152

)(0.186

)(0.186

)(0.186

)(0.264

)(0.264

)(0.266

)Ln(G

DPpc2)

-0.045

9***

-0.046

1***

-0.044

2***

-0.047

7***

-0.046

5***

-0.045

3**

-0.043

1**

-0.050

1**

(0.005

19)

(0.012

1)(0.014

8)(0.014

9)(0.014

9)(0.021

1)(0.021

1)(0.021

2)Open

ness

0.07

89**

*0.07

57**

0.07

29*

0.08

12**

0.07

29*

0.08

110.06

440.08

14(0.014

6)(0.033

0)(0.040

6)(0.040

7)(0.040

3)(0.058

2)(0.057

2)(0.057

6)Ln(P

OP)

-0.146

**-0.138

-0.147

-0.128

-0.138

-0.137

-0.158

-0.119

(0.059

9)(0.139

)(0.170

)(0.171

)(0.171

)(0.242

)(0.241

)(0.246

)Ln(L

ANCAP)

-0.243

***

-0.252

***

-0.249

**-0.256

**-0.249

**-0.256

*-0.242

-0.256

*(0.037

6)(0.087

1)(0.107

)(0.107

)(0.107

)(0.152

)(0.152

)(0.152

)Enforcem

ent(G

over

.E↵ec

t)-0.00714***

-0.00733***

-0.00741**

-0.00729**

-0.00729**

-0.00741*

-0.00742*

-0.00717*

(0.00103)

(0.00238)

(0.00291)

(0.00293)

(0.00293)

(0.00414)

(0.00413)

(0.00421)

Environmen

talLaw

s-0.000515***

-0.000520***

-0.000499***

-0.000541***

-0.000520***

-0.000519**

-0.000479**

-0.000564**

(5.17e-05)

(0.000118)

(0.000140)

(0.000149)

(0.000144)

(0.000207)

(0.000191)

(0.000218)

Enforcem

entxLaw

s6.34e-06***

6.40e-06***

6.13e-06***

6.67e-06***

6.41e-06***

6.38e-06***

5.87e-06**

6.97e-06***

(6.01e-07)

(1.38e-06)

(1.65e-06)

(1.74e-06)

(1.69e-06)

(2.42e-06)

(2.28e-06)

(2.54e-06)

Con

stan

t-11.34

***

-11.50

***

-11.23

***

-11.79

***

-11.47

***

-11.56

**-10.90

**-12.03

**(1.192

)(2.764

)(3.374

)(3.398

)(3.401

)(4.794

)(4.805

)(4.874

)

Observations

15,526

2,91

41,94

51,93

91,94

497

097

596

9R-squ

ared

0.04

20.04

40.04

10.04

60.04

30.04

40.03

80.04

9Number

ofis

2,25

542

328

228

228

214

114

114

1Country-sec

tor,

timeFE

YES

YES

YES

YES

YES

YES

YES

YES

Countries

all

all

all

all

all

all

all

all

Table31:Environmen

tallawsallsubjectsonNO2em

issions

Note:

Rob

ust

stan

darderrors

arein

brackets,

***,

**,*den

otes

statisticalsign

ificance

atthe1,

5an

d10

percent

level,re-

spectively.

Specification

sof

themod

elarewith

allcountries

(1)All

environmentallaws.

(2)Air

and

atmosphere,

Energy,

Env

iron

mentgeneral

(3)Energy,Env

iron

mentgeneral

(4)Air

andatmosphereEnv

iron

mentgeneral

(5)Energy

Air

andatmo-

sphere(6)Env

iron

mentgeneral

(7)Energy

(8)Airan

datmosphere.

Intheisdim

ension

,iden

otes

country,sden

otes

thesubject

ofthelaw

(Air

andAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.).

59

SO2EM

ISSIO

NS

OLS

Leg

islation

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

VARIA

BLES

ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)ln(SO2p

c)

Ln(G

DPpc)

-0.595***

-0.611***

-0.621***

-0.605***

-0.608***

-0.618***

-0.624***

-0.592***

(0.0491)

(0.113)

(0.139)

(0.139)

(0.139)

(0.197)

(0.198)

(0.197)

Ln(G

DPpc2)

-0.0460***

-0.0471***

-0.0478***

-0.0466***

-0.0468***

-0.0476***

-0.0481***

-0.0456***

(0.00369)

(0.00853)

(0.0105)

(0.0105)

(0.0105)

(0.0149)

(0.0149)

(0.0149)

Openness

0.00360

0.000536

0.000960

-0.000727

0.00135

-0.00119

0.00307

-0.000393

(0.0153)

(0.0355)

(0.0435)

(0.0438)

(0.0435)

(0.0623)

(0.0614)

(0.0622)

Ln(P

OP)

0.496***

0.504***

0.502***

0.502***

0.507***

0.497***

0.508***

0.507***

(0.0451)

(0.104)

(0.127)

(0.128)

(0.128)

(0.181)

(0.180)

(0.184)

Ln(L

ANCAP)

-0.0958***

-0.100

-0.0980

-0.0990

-0.104

-0.0926

-0.103

-0.105

(0.0339)

(0.0782)

(0.0959)

(0.0959)

(0.0960)

(0.136)

(0.136)

(0.137)

Enforcem

ent(G

over

.E↵ec

t.)

-0.00520***

-0.00510**

-0.00504*

-0.00510*

-0.00515*

-0.00499

-0.00509

-0.00521

(0.000984)

(0.00229)

(0.00281)

(0.00282)

(0.00280)

(0.00402)

(0.00397)

(0.00400)

Environmen

talLaw

s-0.000403***

-0.000405***

-0.000411***

-0.000408***

-0.000396***

-0.000423**

-0.000400**

-0.000393*

(4.74e-05)

(0.000110)

(0.000133)

(0.000138)

(0.000135)

(0.000193)

(0.000184)

(0.000199)

Enforcem

entxLaw

s4.68e-06***

4.70e-06***

4.75e-06***

4.76e-06***

4.61e-06***

4.90e-06**

4.61e-06**

4.61e-06**

(5.44e-07)

(1.28e-06)

(1.54e-06)

(1.61e-06)

(1.56e-06)

(2.26e-06)

(2.12e-06)

(2.31e-06)

Con

stan

t-21.61***

-21.80***

-21.80***

-21.73***

-21.86***

-21.66***

-21.93***

-21.80***

(0.887)

(2.038)

(2.489)

(2.509)

(2.505)

(3.542)

(3.535)

(3.595)

Observations

15,529

2,907

1,937

1,936

1,941

966

971

970

R-squ

ared

0.067

0.070

0.071

0.069

0.071

0.069

0.073

0.068

Number

ofis

2,255

423

282

282

282

141

141

141

Country-sec

tor,

timeFE

YES

YES

YES

YES

YES

YES

YES

YES

Countries

all

all

all

all

all

all

all

all

Table32:Environmen

tallawsallsubjectsonSO2em

issions

Note:

Rob

ust

stan

darderrors

arein

brackets,

***,

**,*den

otes

statisticalsign

ificance

atthe1,

5an

d10

percent

level,re-

spectively.

Specification

sof

themod

elarewith

allcountries

(1)All

environmentallaws.

(2)Air

and

atmosphere,

Energy,

Env

iron

mentgeneral

(3)Energy,Env

iron

mentgeneral

(4)Air

andatmosphereEnv

iron

mentgeneral

(5)Energy

Air

andatmo-

sphere(6)Env

iron

mentgeneral

(7)Energy

(8)Airan

datmosphere.

Intheisdim

ension

,iden

otes

country,sden

otes

thesubject

ofthelaw

(Air

andAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.).

60

PM

2.5

EM

ISSIO

NS

OLS

Leg

islation

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

VARIA

BLES

ln(P

M2.5p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)ln(P

M2.5p

c)

Ln(G

DPpc)

-0.052

7***

-0.051

2-0.051

2-0.049

3-0.053

1-0.047

5-0.055

0-0.051

1(0.014

3)(0.033

1)(0.040

7)(0.040

7)(0.040

6)(0.058

1)(0.057

7)(0.057

9)Ln(G

DPpc2)

-0.006

59**

*-0.006

29**

-0.006

32**

-0.006

10*

-0.006

44**

-0.005

98-0.006

66-0.006

21(0.001

13)

(0.002

61)

(0.003

20)

(0.003

20)

(0.003

20)

(0.004

57)

(0.004

54)

(0.004

56)

Open

ness

0.04

66**

*0.04

82**

0.04

78*

0.04

73*

0.04

97*

0.04

540.05

030.04

92(0.008

92)

(0.020

6)(0.025

4)(0.025

2)(0.025

4)(0.035

9)(0.036

4)(0.035

9)Ln(P

OP)

-0.842

***

-0.843

***

-0.842

***

-0.843

***

-0.843

***

-0.842

***

-0.843

***

-0.843

***

(0.005

98)

(0.013

9)(0.017

0)(0.017

0)(0.017

0)(0.024

3)(0.024

2)(0.024

2)Ln(L

ANCAP)

-0.082

3***

-0.085

0**

-0.085

9*-0.085

6*-0.083

6*-0.087

8-0.083

9-0.083

3(0.016

9)(0.039

0)(0.047

9)(0.047

8)(0.048

0)(0.068

1)(0.068

4)(0.068

2)Enforcem

ent(G

over

.E↵ec

t.)

0.00133***

0.00139***

0.00137**

0.00136**

0.00143***

0.00130*

0.00143*

0.00143*

(0.000190)

(0.000439)

(0.000540)

(0.000538)

(0.000539)

(0.000768)

(0.000771)

(0.000763)

Environmen

talLaw

s0.000123***

0.000127***

0.000126***

0.000130***

0.000126***

0.000129**

0.000122**

0.000131***

(1.23e-05)

(2.86e-05)

(3.53e-05)

(3.49e-05)

(3.52e-05)

(4.98e-05)

(5.05e-05)

(4.96e-05)

Enforcem

entxLaw

s-1.96e-06***

-2.02e-06***

-1.99e-06***

-2.06e-06***

-2.01e-06***

-2.04e-06***

-1.94e-06***

-2.08e-06***

(1.53e-07)

(3.57e-07)

(4.38e-07)

(4.36e-07)

(4.38e-07)

(6.21e-07)

(6.27e-07)

(6.20e-07)

Con

stan

t-0.511

***

-0.535

-0.538

-0.528

-0.538

-0.528

-0.548

-0.527

(0.142

)(0.327

)(0.402

)(0.402

)(0.401

)(0.573

)(0.572

)(0.571

)

Observations

8,84

51,65

61,10

41,10

21,10

655

055

455

2R-squ

ared

0.66

00.66

50.66

30.66

50.66

60.66

20.66

40.66

7Number

ofis

2,25

342

228

128

128

214

014

114

1Country-sec

tor,

timeFE

YES

YES

YES

YES

YES

YES

YES

YES

Countries

all

all

all

all

all

all

all

all

Table33:Environmen

tallawsallsubjectsonPM2.5

emissions

Note:

Rob

ust

stan

darderrors

arein

brackets,

***,

**,*den

otes

statisticalsign

ificance

atthe1,

5an

d10

percent

level,re-

spectively.

Specification

sof

themod

elarewith

allcountries

(1)All

environmentallaws.

(2)Air

and

atmosphere,

Energy,

Env

iron

mentgeneral

(3)Energy,Env

iron

mentgeneral

(4)Air

andatmosphereEnv

iron

mentgeneral

(5)Energy

Air

andatmo-

sphere(6)Env

iron

mentgeneral

(7)Energy

(8)Airan

datmosphere.

Intheisdim

ension

,iden

otes

country,sden

otes

thesubject

ofthelaw

(Air

andAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.).

61

WATER

POLLUTIO

NOLS

Leg

islation

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

VARIA

BLES

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

ln(W

ater

poll.pc)

Ln(G

DPpc)

-0.157**

-0.157

-0.155

-0.162

-0.155

-0.161

-0.162

-0.148

(0.0652)

(0.152)

(0.187)

(0.189

)(0.186

)(0.270

)(0.272

)(0.264

)Ln(G

DPpc2)

-0.0253***

-0.0251*

-0.0249

-0.025

3-0.025

2-0.025

6-0.025

0-0.024

8(0.00567)

(0.0132)

(0.0162)

(0.016

3)(0.016

2)(0.023

3)(0.023

4)(0.023

2)Openness

2.208***

2.146***

2.104***

2.16

4***

2.17

3***

2.23

5**

2.10

1**

2.11

0**

(0.213)

(0.485)

(0.590)

(0.601

)(0.598

)(0.873

)(0.850

)(0.839

)Ln(P

OP)

-0.285***

-0.279**

-0.276*

-0.277

*-0.286

*-0.287

-0.268

-0.285

(0.0528)

(0.122)

(0.151)

(0.151

)(0.150

)(0.216

)(0.217

)(0.214

)Enforcem

ent(G

over

.E↵ec

t.)

-0.00116

-0.00114

-0.00109

-0.001

08-0.001

26-0.001

27-0.000

898

-0.001

30(0.000938)

(0.00217)

(0.00269)

(0.002

65)

(0.002

66)

(0.003

77)

(0.003

85)

(0.003

87)

Environmen

talLaw

s-9.19e-05**

-9.84e-05

-0.000103

-8.34e-05

-0.000

110

-9.27e-05

-7.37e-05

-0.000

136

(4.12e-05)

(9.45e-05)

(0.000127)

(0.000

113)

(0.000

110)

(0.000

145)

(0.000

185)

(0.000

177)

Enforcem

entxLaw

s1.15e-06**

1.15e-06

1.17e-06

1.01

e-06

1.31

e-06

1.17

e-06

8.51

e-07

1.51

e-06

(5.14e-07)

(1.20e-06)

(1.58e-06)

(1.43e-06)

(1.45e-06)

(1.92e-06)

(2.25e-06)

(2.29e-06)

Con

stan

t-9.648***

-9.494***

-9.374***

-9.632

***

-9.478

***

-9.736

***

-9.547

***

-9.199

**(0.869)

(2.023)

(2.452)

(2.501

)(2.512

)(3.663

)(3.505

)(3.532

)

Observations

5,108

957

639

637

638

318

319

320

R-squ

ared

0.138

0.136

0.135

0.13

60.13

70.13

90.13

40.13

6Number

ofis

1,168

219

146

146

146

7373

73Cou

ntry

sector

andtimedummies

YES

YES

YES

YES

YES

YES

YES

YES

Cou

ntries

all

all

all

all

all

all

all

all

Table34:Environmen

tallawsallsubjectsonWaterpollution

Note:

Rob

ust

stan

dard

errors

arein

brackets,

***,

**,*den

otes

statisticalsign

ificance

atthe1,

5an

d10

percent

level,

respectively.Specification

sof

themod

elarewithallcountries

(1)Allenvironmentallaws.

(2)Env

iron

mentgeneral,Water

and

Waste

and

hazardou

ssubstan

ces(3)Water,Env

iron

mentgeneral

(4)Water

and

Waste

and

hazardou

ssubstan

ces(5)

Env

iron

mentgeneral

andWaste

andhazardou

ssubstan

ces(6)Waste

andhazardou

ssubstan

ces(7)Water

(8)Env

iron

ment

general.In

theis

dim

ension

,iden

otes

country,sden

otes

thesubject

ofthelaw

(Air

andAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.).

62

FOREST

AREA

OLS

Leg

islation

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

VARIA

BLES

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

ln(Forestpc)

Ln(G

DPpc)

0.100***

0.101***

0.100***

0.102***

0.102***

0.1000*

0.101*

0.104*

(0.0133)

(0.0309)

(0.0378)

(0.0380)

(0.0380)

(0.0538)

(0.0538)

(0.0543)

Ln(G

DPpc2)

0.00816***

0.00826***

0.00818**

0.00830**

0.00831**

0.00817*

0.00819*

0.00843*

(0.00115)

(0.00268)

(0.00328)

(0.00330)

(0.00329)

(0.00467)

(0.00466)

(0.00470)

Openness

-0.0254***

-0.0252***

-0.0252**

-0.0251**

-0.0254**

-0.0248

-0.0255

-0.0253

(0.00419)

(0.00970)

(0.0119)

(0.0119)

(0.0119)

(0.0168)

(0.0170)

(0.0169)

Ln(L

ANCAP)

1.124***

1.124***

1.124***

1.124***

1.124***

1.123***

1.125***

1.124***

(0.0274)

(0.0633)

(0.0777)

(0.0777)

(0.0776)

(0.111)

(0.110)

(0.110)

Enforcem

ent(G

over

.E↵ec

t.)

6.31e-06

-3.36e-06

-6.46e-06

-1.19e-05

7.92e-06

-2.77e-05

1.33e-05

2.68e-06

(0.000119)

(0.000275)

(0.000340)

(0.000338)

(0.000335)

(0.000487)

(0.000480)

(0.000474)

Environmen

talLaw

s-2.21e-05***

-2.35e-05**

-2.25e-05*

-2.51e-05*

-2.30e-05*

-2.48e-05

-2.04e-05

-2.55e-05

(4.50e-06)

(1.09e-05)

(1.35e-05)

(1.35e-05)

(1.32e-05)

(1.96e-05)

(1.88e-05)

(1.88e-05)

Enforcem

entxLaw

s3.47e-07***

3.66e-07**

3.58e-07*

3.87e-07**

3.55e-07*

3.93e-07

3.27e-07

3.83e-07

(6.37e-08)

(1.54e-07)

(1.90e-07)

(1.91e-07)

(1.86e-07)

(2.79e-07)

(2.63e-07)

(2.65e-07)

Con

stan

t-0.885***

-0.885***

-0.889**

-0.888**

-0.878**

-0.899

-0.879

-0.877

(0.135)

(0.312)

(0.383)

(0.382)

(0.382)

(0.545)

(0.544)

(0.542)

Observations

15,027

2,821

1,881

1,881

1,880

941

940

940

R-squ

ared

0.703

0.703

0.703

0.703

0.703

0.703

0.703

0.704

Number

ofis

2,191

411

274

274

274

137

137

137

Country-sec

tor,

timeFE

YES

YES

YES

YES

YES

YES

YES

YES

Countries

all

all

all

all

all

all

all

all

Table35:Environmen

tallawsallsubjectsonForest

area

Note:

Rob

ust

stan

dard

errors

arein

brackets,

***,

**,*den

otes

statisticalsign

ificance

atthe1,

5an

d10

percent

level,

respectively.Specification

sof

themod

elarewithallcountries

(1)Allenvironmentallaws.

(2)Forestry,

Lan

dan

dSoilan

dEnv

iron

mentgeneral

(3)Forestryan

dEnv

iron

mentgeneral

(4)Forestryan

dLan

dan

dSoil.

(5)Forestry(6)Env

iron

ment

general.(7)Lan

dan

dSoil.

Intheis

dim

ension

,iden

otes

country,sden

otes

thesubject

ofthelaw

(Air

andAtm

osphere,

Env

.Gen

.,Forestry,

Water,etc.).

63

10 First stage estimation Income and Openness

To overcome the simultaneity problems of the environmental outcomes with the degree ofopenness (international trade) and income (GDP), in a first stage we used an instrumen-tation of these two variables. Using the geographic variables in the case of the former andusing human capital formation, investment and population in the later.

The geographic variables are good instrumental variables as noted by Frankel and Romer(1999). And the instruments for GDP are taken from the growth literature (Grossmanand Krueger (1994)). We do this in a first stage, because our data vary according to coun-tries, subjects and time. Since openness varies according to importer countries, exportercountries and time, we need to do this in a previous stage and then we add the predictedvariable in a country-time dimension.

From growth empirics we use Equation 6 to obtain the predicted value of income percapita( ˆln(GDPpc), this variable is obtained after the regression using as explanatory variablespopulation (ln(POP )it), lag of GDP (ln(GDPpc)i,t�1), share of investment (ln(I/GDP )it),growth rate of population (nit), rate of primary school enrolment (ln(school1)it), rate ofsecondary school enrolment ((school2)it) and an error term (µit) as in Equation 6 be-low.

ln(GDP/POP )it = �0 + �1ln(POP )it + �2ln(GDPpc)i,t�1+

�3ln(I/GDP )it + �4nit + �5ln(school1)it + �6(school2)it + µit(6)

The predicted multilateral openness and the bilateral trade variables used in Equation 1are obtained from a gravity model of trade, which is estimated using a large panel-dataseton pair-wise trade flows. The standard gravity model states that trade between countriesis positively determined by their size (GDP, population and land area) and negativelydetermined by geographical and cultural distance.

The geographical variables are exogenously determined and hence are suitable instrumentsfor trade (Frankel and Romer (1999)). We follow Badinger and Breuss (2008) specifica-tion of the gravity model, in which bilateral openness is regressed on countriesAo popula-tions (ln(POP )it, ln(POP )jt), land capacity (area) (ln(Landcapi/ Landcapj)ij), distance(ln(Dist)ij), a common border dummy (ln(Adj)ij), a common language dummy ((Lang)ij)and a landlocked variable ((Landlok)ij= sum of a landlocked dummy of countries i and j).Two other variables are included in order to be consistent with the theoretical model: ameasure of similarity of country size (ln(Landcapi/ Landcapj)ij) and remoteness from the

64

rest of the world (Ln(Remoteness)ij).20

ln(tradeijt/GDPit) = �i + �j + 't + �1ln(POP )it + �2ln(POP )jt+

�3ln(Dist)ij + �4ln(Adj)ij�5(Area)ij + �6(Lang)ij + �7(Landborder)ij+

�8(Landlok)ij + �9ln(Landcapi/Landcapj)ij + �10ln(Remoteness)ij+

µijt

(8)

Finally, from Equation 8 the exponent of the fitted values across bilateral trading partners( ˆTijt) is aggregated to obtain a prediction of total trade for each country and year.

Tijt =X

exp( ˆTijt) (9)

Both, the bilateral prediction ( ˆTijt) and the aggregated bilateral prediction (Tijt) are usedas regressors in the model with ijt dimension. Equation 8 and ( ˆTijt) is also used in modelof Equation 1. By using these predicted values we are able to isolate the part of tradethat is explained exclusively by geographical, cultural and country-specific factors. Otherpolicy changes that could also explain trade variations are relegated to the unexplainedpart of the model (error term).

20

Remoteij = 0.5DCCij [Ln(

NX

k=1,k 6=j

(Distik)/(N � 1))] + [Ln(NX

k=1,k 6=i

(Distkj)/(N � 1))] (7)

Where D

(CC) is a common continent dummy. This variable will then be equal to zero if countries are on

the same continent. Remote is then the log of the average value of the average distances of countries i andj from all other countries.

65