LAND OWNERSHIP INEQUALITY AND RURAL UNREST: EVIDENCE FROM THE LATIFUNDIA REGIONS OF SPAIN BEFORE THE CIVIL WAR

Jordi DomènechDepartment of Economic HistoryUniversidad Carlos III de MadridCalle Madrid 12628903 GETAFE (Madrid)SPAIN

Email: jdomenec@clio.uc3m.esTel: (+34) 91 624 9809

***very preliminary draft, not for quotation****

INTRODUCTION

The Second Republic in Spain (1931-1936) witnessed one of the fastest and

deepest processes of popular mobilization in interwar Europe. The General

Workers’ Union (UGT) jumped from around 230’000 members in 1929 to more

than a million members in 1932. Similarly, despite losing a large share of peasant

workers to the socialists, the anarcho-syndicalist National Confederation of Labour

(CNT) managed to unite about another million workers in the second half of 1931.

As a result, union density jumped from its previous peak of 15 per cent of the

gainfully employed in 1920 to almost 30 per cent in 1932, below the levels of

mobilization of the Scandinavian countries but above the union density levels of

Britain, France or Belgium in the 1920s (at a lower level of development) (union

densities in Mann, 1995). In addition, strike activity also jumped to unprecedented

levels, reaching in 1933 or in 1936 levels of strike intensity only comparable to

Italy during the biennio rosso of 1919-1920 or in Britain in 1926.

Being still a predominantly agrarian country, by 1930 about half of the

population worked in agriculture, this fast process of mobilization involved the

mobilization of the agricultural workers. Although by no means a general

phenomenon, large parts of Spain, especially in the centre and the south where

dry-farming was predominant, were characterized by a distribution of property

dominated by large estates, employing labourers or renting parts of the estate to

sharecroppers. Anarcho-syndicalists had traditionally had a strong presence in

some large agricultural towns in the cereal-growing plains of Córdoba, although

1

the Socialists were capable of recruiting a growing share of landless labourers or

sharecroppers. In the early 1930s, the National Federation of Peasants (Federación

Nacional de Trabajadores de la Tierra) reached out to more than 400,000

members. Furthermore, peasants represented a 34 per cent of strikers in 1932 and

29 per cent in 1933.

There is no doubt this unprecedented mobilization of peasants had

enormous and tragic political consequences. In European history, peasant

rebellion has been linked to revolution and civil war, especially when the

mobilization of the peasanty revolves around the issue of land ownership.

Democratic and popular threats to the landowning elites has been the core issue of

the hegemonic accounts of transitions to authoritarian regimes and the collapse of

democracies in interwar Europe. Some examples of this literature are Alexander

Gerschenkron’s Bread and democracy in Germany (1943), Barrington Moore’s

Social origins of dictatorship and democracy (1966), Gregory Luebbert’s Liberalism,

Fascism or Social Democracy (1991) or Daron Acemoglu and James Robinson’s

Economic origins of Dictatorship and Democracy (2005).

The most eloquent statement on the effect of peasant mobilization and

agrarian reform on the collapse of the Second Republic and the beginning of the

civil war (1936-1939) is no doubt Edward Malefakis’ classic Agrarian reform and

peasant revolution in 20th Century Spain: origins of the Spanish civil war (1970). In

the book, Malefakis argues reactionary forces were united by the Republican

programme of land confiscation. In addition, peasant workers mobilized and

radicalized because bureaucratic and fiscal problems coupled with landowners’

natural opposition to agrarian reform slowed down, almost to halt, the programme

of land re-distribution. These polarizing forces exploded in 1936, when a new

centre-left government was elected after two years with conservative

governments. In July 1936, the Civil War broke out. In Malefakis view, the

conservative reaction to land confiscation and to social revolution in the country

side caused the collapse of Spanish democracy.

2

AIMS OF THIS PAPER

This paper for obvious reasons does not intend to settle the enormous literature

on the origins of the Spanish civil war, but shed some light on the characteristics

and the causes of social conflict in the dry-farming regions of Spain, characterized

by the important, but by no means homogenously predominant, presence of large

estates or latifundia. To do so I focus on rural strikes and land invasions in the

provinces of Córdoba, Jaén and Sevilla (see graph below).

My unit of analysis is the town and my approach is simply counting the

number of events related to rural conflict associated with a given town. This is far

from ideal for obvious reasons. Although the number of events is probably

correlated with conflict intensity, this correlation is certainly less than one. Strikes

vary in duration, extension and support. However, duration is in many instances

endogenous to the probability of success (in most exercises with strike data, the

duration of the strike is negatively correlated with the probability of success, Card

and Olson, 1995; Young and Huberman, 2001; Friedman, 1988). The extension of

strike does not seem to be a problem because most strikes were organized at the

municipal level, rather than aimed at a particular employer. Support is more

problematic, because several strikes were not followed by all the agricultural

workers of a given town. Support however was also endogenous to the success of

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the strike, since violence and social penalties against strikebreakers and

abstentionists were part of the same process of striking.

In addition, in a context in which detailed historical evidence is sparse,

counting events has traditionally been used as a second-best substitute. Examples

abound, although perhaps the most famous example is Eric Hobsbawm and George

Rude’s 1969 book Captain Swing. Other examples are John Markoff’s work on

revolts in the French Revolution (Markoff, 1985, 1986) or recent work on land

conflicts and invasions in Brazil (Alston, Libecap, Mueller, 2000; Hidalgo, Naidu,

Nichter, Richardson, 2010). For rural conflicts in Republican Spain, as far as I

know, only Bernal (1974) followed this method. It is clear as well that a

quantitative approach needs to be balanced with a more qualitative approach to

understand the issues, the dynamics of mobilization and the probabilities of

success or failure.

Data for this paper were collected from the secondary literature (Pérez

Yruela, 1979; Pascual Cevallos, 1983; Cobo Romero, 1992) and newspapers like el

Sol (published in Madrid), La Vanguardia (published in Barcelona), or ABC (both

the Madrid and Sevilla editions) which had very detailed sections on events in the

provinces which are quite consistent across all the newspapers. In table 1, I

provide the correlations and rank-order-correlation of the number of hits in

boolean searches in the digital archives of those newspapers between 1931 and

1934.

Table 1. Correlations of newspaper hits.

. correlate LAVANGUARDIA ELSOL ABCMADRID ABCSEVILLA

| LAVANG~A ELSOL ABCMAD~D ABCSEV~A-------------+------------------------------------LAVANGUARDIA | 1.0000 ELSOL | 0.8644 1.0000 ABCMADRID | 0.8626 0.9893 1.0000 ABCSEVILLA | 0.8248 0.9749 0.9769 1.0000

. spearman LAVANGUARDIA ELSOL ABCMADRID ABCSEVILLA

| LAVANG~A ELSOL ABCMAD~D ABCSEV~A

4

-------------+------------------------------------LAVANGUARDIA | 1.0000 ELSOL | 0.8532 1.0000 ABCMADRID | 0.8476 0.8736 1.0000 ABCSEVILLA | 0.7629 0.7940 0.7546 1.0000

Information on strikes and land invasions has relied mostly on newspapers

in the case of the province of Sevilla. The classic reference for Sevilla, Pérez

Cevallos (1983), although it gives the total number of conflicts, does not give the

full break down of conflicts at the provincial level. The number of strikes and land

invasions identified with the newspapers is close enough to the total number of

conflicts uncovered by Pascual Cevallos to justify relying exclusively on the

national press. Pérez Yruela (1979) and Cobo Romero (1932) give very detailed

information on towns in Córdoba and Jaén and his information is superior in

coverage to the information provided by the newspapers, with the exception of

general strikes, in which I have relied on the summaries of prefect report of

published in the newspapers to identify the towns participating in the general

strikes. Table 2 gives the breakdown of rural strikes in the provinces according to

Francisco Cobo Romero (1992), which has to be read as a a relatively “generous”

quantification of the total number of strikes (because it also uses in some cases the

socialist press). With the data set I have assembled I am able to track down about

75 per cent of the strikes reported for the period 1931 to 1934.

Table 2. Number of rural strikes in Córdoba, Jaén and Sevilla

Córdoba Jaén Sevilla Totals

1931 69 72 48 189

1932 32 110 75 217

1933 100 195 60 355

1934 53 135 32 220

1935 0 1 1 2

1936 29 19 22 70

Source: Cobo Romero, Revolución campesina y contrarrevolución franquista, p. 85.

Once this information was processed, the objective was linking the strike

and land invasion data to the characteristics of towns in order to uncover:

5

a. which workers in which towns protested more often, the distribution of

strikes.

b. A first attempt to answer why? I exploit in this paper certain institutional

characteristics of labour markets in the 1930s to isolate some of the factors

explaining protest in the 1930s.

EXPLANATIONS OF CONFLICTS AND RESEARCH DESIGN

Historians of Andalusian protest have focussed on two main sources of discontent,

which are in fact related. The most important one is harvest failure in a context in

which most landless workers did not have alternative sources of income. The

second one is the failure of the Republic to re-distribute land. In this setting,

harvest failure would obviously increase the pressure to re-distribute land to the

hungry peasants.

In his classic book on the history of conflicts in Córdoba, Juan Díaz del Moral

(the notary of Bujalance, in Córdoba) in 1928 dismissed the view that harvest

failures were a trigger of conflict and instead posited that in years of good harvests

typically raised protest. Moreover, in his view Córdoba and Andalucía was not the

agricultural and traditional backwater that several foreign journalists had depicted

when describing the events of the Mano Negra in the early 1880s or the Jerez

revolt of 1892, but rather a rapidly changing agricultural economy (Díaz del moral,

1973: 20). In his view, moreover, access to land was changing and the reliance of

large estates on labourers was changing as parts of latifundia in relatively well

functioning land markets or were rented to sharecroppers.

Following this line of reasoning, James Simpson and Juan Carmona shifted

the focus of attention from traditional accounts based on the backwardness of

Andalucía to the analysis of a well-functioning labour market with particular

characteristics (Carmona and Simpson, 2003: chapter 3). In their view, the chief

characteristic of Andalusian labour markets were the large changes in labour

demand. Demand peaked in harvest times for cereals and olives, and was generally

low outside harvest (with some exceptions). Therefore, Andalusian landless

labourers only were employed for about 180-200 days a year. In this context, large

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employers also relied on temporary workers and in fact there was a very active

pattern of temporary labour migrations looking for work in the main harvests of

cereals, olives and vines. In Simpson and Carmona’s view (and in Díaz del Moral’s),

the main conflict was between local and temporary workers (forasteros) and

between the temporary workers and the workers permanently employed in the

large farms. The area sown grew constantly in the first three decades of the 20th

century and mechanization of harvest work in cereals was only modest, therefore

there was no surplus of workers in the Andalusian provinces. Rather, as unions

wanted to stabilize and negotiate working conditions, it was necessary to restrict

the presence of temporary workers, who undercut wages and working conditions

and broke strikes. Collective bargaining in this case basically had a re-distributive

effect away from the atomised temporary migrants to the local, organized workers.

In their view, it was the ‘exogenous’ arrival of working class ideologies that

disrrupted the normal functioning of relatively efficient and well-functioning

labour market for agricultural labourers.

The 1930s saw a further twist to the evolution of labour markets in

Andalucía. Until 1919, local workers, generally repressed by the police, had been

unable to prevent the movement of temporary migrants. It was only in the wave of

strikes of 1918 and especially 1919 that workers, especially in Córdoba, had been

able to restrict the employment of temporary migrants. The arrival of the Spanish

Socialist party to power in 1931 (in a coalition with the Centre-Left Republicans),

however, meant a very substantial increase in the regulation of labour markets,

and especially of rural labour markets. Firstly, the law of municipal boundaries (ley

de términos municipales), finally derogated in May 1934, forbade the recruitment

of transient migrants and workers from other towns if there were local workers

unemployed. Second, the worker employment law of October 1931 (ley de

ocupación obrera) meant that the local conciliation board -dominated by the

unions and the mayor- organized the list of employable workers and established

who was going to get the next available job (the “turno”). Although both laws

certainly were not fully enforced, the qualitative evidence suggests strongly that

enforcement was high enough to guarantee a virtual closed shop in the main rural

labour markets. This was also the case in anarcho-syndicalist holds, where the

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unions did not support collective bargaining but were staunch defenders of the

municipal boundaries law and the turno. No doubt, membership exploded. I can

think of better “selective incentives” to join (a death threat), but a closed shop

seems to be enough of an incentive (Lichbach, 1994).

This distributional impact can also be coupled with other triggers of

collective action. Recently, economists and political scientists have explicitly

formulated testable hypothesis on the origins of conflict. Just to mention a recent

one, Hidalgo, Naidu, Nichter and Richardson (2010) tried to explain land invasions

in Brazil as a response to harvest failure or income declines. In their study, they

capture “exogenous” variations in living standards by instrumenting income with

rainfall, assuming that agricultural incomes will be subject to substantial variation

caused by weather conditions. In their study, they also see that the probability of

invading is also higher, the bigger the inequality in the distribution of land

holdings. Unexpected declines in living standards and land ownership inequality

brought about higher levels of rural conflict. In Spain, as dry-farming agricultural

output was quite volatile and land ownership distribution was apparently very

unequal, it is probably worthwhile to test these two hypotheses.

The new institutional economics also offers an alternative view of rural

conflict which will be relevant to the historical context of 1930s Spain. Alston,

Libecap, and Mueller (2000) for example argue that legal inconsistencies in land

reform policies in Brazil led to an increase in violent conflict between landowners

and squatters and to the deforestation of the Amazon forest. Posing a threat to

established property rights, in this view, the land reform pushed by the Republican

authorities potentially had dramatic effects in areas with a highly skewed land

ownership distribution.

My approximation to the determinants of strikes and land invasions

therefore takes into account the insights from the historical and social science

literature on the origins of conflicts. To do so I exploit first the relatively exogenous

variation in the land ownership distribution (determined to a great extent in a

period before the explosion of rural conflict in the 1930s), which one the one hand

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captures the effect of inequality on conflict and also could be related to the ability

of strikers to detect strikebreakers in large estates as opposed to the same ability

in scattered landholdings.

Secondly, I exploit variation in population densities, which give an

approximation to the land to labour ratio, in turn giving a further approximation to

the local labour demand that the labourers faced after the passing of the law of

municipal boundaries in 1931. In this context, the situation is closed to a quasi

experiment, since area and population (the ingredients of population density)

were determined well before the passing of the law of municipal boundaries.

Wages were determined by provincial collective contracts, negotiated every year

(Anuario Español de Política Social, 1935). To the point that wages reflected the

local labour supply and demand equilibrium of the towns with an average land to

labour ratio, adjustments in the local labour markets of towns with low land to

labour ratios will take the form of unemployment (via quantities rather than

prices). On the other hand, in the long run, population decisions are endogenous,

therefore landless workers will tend to concentrate in large towns with relatively

thick labour markets (develop).

HARVEST FAILURE

Jaén, Córdoba and Sevilla especialised in a combination of wheat and olives. In

Córdoba in 1932, 35 per cent of the agricultural land was used to grow wheat, 37

per cent olive trees, and 16 per cent was left fallow. Only 12 per cent of the land

had alternative uses. In Jaén, in the same year, 26 per cent of the agricultural land

was left fallow, 27 per cent was used to grow cereals and 42 per cent to grow olive

trees. Only 5 per cent of the land was left for alternative crops. In Sevilla, 43 per

cent was cereal, 35 per cent was olive trees and 8 per cent was fallow. 14 per cent

of the land was left for alternative uses (all data from the Anuario Estadístico,

1932-1933). The vulnerability of these provinces to crop failure is obvious.

I first look at aggregate trends in production of cereals and olives (Carreras

and Tafunell, 2005). In both cases, output trends up with substantial fluctuations,

which are especially acute in the olive crops (in this case proxied by the production

9

of olive oil). Graph 1 gives the trends in total production since 1890 (Jaén and

Córdoba were the main producers of olive oil by a large margin).

Graph 2. Olive oil and wheat production (index numbers, 1890=100)01002003004005001890189519001905191019151920192519301935yearindexwheatindexoliveoilIn this case, aggregate olive output is basically tracking the output produced

by Córdoba and Jaén, and to a lesser extent Sevilla. 1926, 1928 and 1930 were

cases of substantial crop failure, whereas the 1933 crop was poor but not

dramatically poor. There were two spectacular spikes in 1927 and 1928. When I

look at the average production of olives per province between 1922 and 1934

(when the Spanish statistical yearbooks gave information on production at the

provincial level), only two years in each province appear to be one standard

deviation below the mean (the calculation takes into account the greater amount of

land used to grow olives). For both Sevilla and Córdoba, between 1922 and 1934,

1928 and 1930 were the only two years in which the harvest of olives was one

standard deviation below the mean (again, calculation takes into account that

more land was available to grow olives), for Jaén, 1930 and 1933 were one

standard deviation below the mean.

Similar inspection of data on cereal harvests shows that for our three

provinces, 1931 and 1933 were particularly bad years, while 1932 and 1934 were

delivered extraordinary harvests. The reason seems to be largely exogenous. The

10

spring temperatures in Andalucía in 1931 and 1933 were particularly high,

compared to the relatively cold spring temperatures of 1932 and 1934, and high

temperatures in Spring have a negative impact on cereal output (temperatures

from Anuario Estadístico 1931, 1932-1933, 1934; Rodríguez,-Puebla, Encinas,

Frías, 2004a,2004b on effects of winter rain and spring temperatures on output).

Also taking into account the amount of land put into production, the harvest of

1931 in Sevilla was well above the mean, while the 1933 harvest was about one

standard deviation below the mean (one could expect a harvest as bad as that one

once in every six years). In Jaén, the 1931 and the 1933 harvests were less than

one standard deviation below the mean. Only in Córdoba was the 1933 harvest

catastrophic, less than 2 standard deviations below the mean, while the 1931

harvest was one standard deviation above the mean. In all three cases, the 1932

harvest was more than 2 standard deviations above the mean.

To what extent do we see largely exogenous crop failures affecting patterns

of conflict? There is no doubt that crop failures must have had serious effects on

the living standards of the workers dependent on paid employment by causing a

collapse in the demand for labour. However, it is far more difficult to link periods

of crop failure to the explosion of rural unrest of the 1930s. For cereals, harvests in

the 1920s were pretty stable and only 1931 and 1933 seem to have been

particularly poor years. In 1933, Córdoba had certainly a very poor harvest, but

strikes and conflict increased also in both Jaén and Sevilla in the same year. On the

other hand, 1932 was an exceptional year, and yet the number of strikes grew from

the previous 1931 level. In 1934, a year of an exceptionally good cereal harvest, the

National Federation of Peasants organized the most serious general strike of its

history. In Jaén, more dependent on olives than the other two provinces,

experienced increases in strikes both in 1932 (a year of a relatively good harvest)

and in 1933 (a year of poor harvest).

LAND INEQUALITY AND POPULATION DENSITIES,

Despite the homogeneous image of being characterized as a latifundia region, the

truth was that the distributions of land ownership varied widely in the three

provinces studied here. Andalucía in this sense was no different than other

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Southern European regions characterized by dry farming. For example, Julian Pitt

Rivers noted “The agricultural land of Andalucía has been held in latifundia, ever

since the Roman times. The complex of dry-farming, with its uncertain yearly

returns and fluctuating demand for manpower, may be seen through the history of

the Mediterranean to have tended to encourage the agglomeration of property, and

also of habitations, into large units. The vast expanse cultivated by short-term,

town-dwelling labour for a single master is common not only in Betica, la Mancha

and Castile, but to much of Italy as well. This type of landholding is typical only of

the plains, and it is rarely found today among the mountains. The soil of the sierra

tends to be poorer than that of the plain and is more labourious to cultivate and

more subject to erosion. In any case, its unevenness makes it unsuitable for large

scale exploitation. (Pitt Rivers, 1954: 39; see as well Braudel, La Méditerranée, vol.

I: 82).”

Data on the distribution of land ownership at the municipal level are taken

from Pascual Carrión’s classic Los latifundios en España (first published in 1932),

which provides information at the municipal level on the fraction of total area

owned by estates of more than 250 hectares (2,5 million square meters or about

330 football pitches). In graph 3 I show the histogram of the distribution of land

ownership for 198 towns (of a total of 272 towns in the three provinces excluding

the cities over 40000 and the capitals of the province). In many towns, the level of

land ownership concentration was actually low.

Graph 3. Historigram, proportion of town are owned by estate of more than 250

hectares (N=198 towns in Jaén, Córdoba, Sevilla).0.005.01.015.02Density0102030405060708090100landinequality12

Landinequality was higher in the fertile plains than in the hills. Indeed, our

crude measure capturing the presence of large estates is negatively correlated with

altitude. Moreover, altitude is also negatively correlated with the presence of

landless labourers in the total population (data from the Censo de Campesinos,

which are clustered at the judicial district level rather than given for each town).

Finally, land ownership inequality is mildly negatively correlated with population.

Table 3 gives the correlations and graph 4 the relationship between ownership

inequality and population.

Table 3. Correlation matrix of of inequality and geographical and demographic

variables. . correlate landinequality pop1930 altitude labourerspop(obs=198)

landin~y pop1930 altitude labourers~p

landinequa~y 1.0000pop1930 -0.1111 1.0000altitude -0.2213 -0.0085 1.0000labourers/pop -0.0747 0.0523 -0.1867 1.0000

Graph 4. Land ownership inequality and population. Lowess smoothing.020406080100landinequality050001000015000200002500030000pop1930bandwidth = .8Lowess smootherMoreover, I look at the distribution of labourers, small owners and

sharecroppers among the Andalucia pueblos, using the Peasant Census (Censo de

13

Campesinos) of 1933. The data are aggregated at the level of judicial district and it

is unclear what was the level at which a landowner was considered a “small

proprietor”. Graphs 5, 6 and 7 give the histograms. Again the picture is one of more

heterogeneity than traditionally assumed, everywhere labourers were far more

prevalent than either small proprietors or sharecroppers, but Córdoba and Jaén

had a higher share of small landowners.

Graph 5. Histogram with the fraction of labourers (fraction of all “poor” peasants,

not of total population in each district).0.05.1.15.2Fraction.5.6.7.8.9fraction labourers

Graph 6. Histogram of fraction of sharecroppers 0.1.2.3Fraction0.1.2.3fraction sharecroppers

14

Graph 7. Histogram fraction of small owners.0.05.1.15.2Fraction0.1.2.3.4fraction small owners

. correlate perlabourers percentsmallowners percentsharecrop

(obs=40)

| perlab~s percen~s percen~p

-------------+---------------------------

perlabourers | 1.0000

percentsma~s | -0.8962 1.0000

percentsha~p | -0.7969 0.4463 1.0000

DETERMINANTS OF STRIKES

When I look at strikes between April 1931 and June 1934, the picture that

emerges is that for a large fraction of towns in some of the most strike-prone

provinces of Spain mobilization and collective action were remote episodes

happening in other parts of the province. Towns in the hills, as already noted by

the Juan Díaz del Moral about the strike wave of 1918-1919, were barely touched

by the new ideologies. 50 per cent of towns in the three provinces did not witness

a single strike or just one strike (in a period that involved at least two large general

strikes). Social relations were considered explosive, but about 50 per cent of towns

can be excluded from this. Graph 8 gives the histogram of the number of times

rural workers in each town struck:

15

Graph 8. Histogram of rural strikes.0.1.2.3.4Density01234567891011strikes

What were the main demands of strikes? Two large groups of strikes emerge. One

the one hand there were several summer and autumn strikes to negotiate the collective

harvest contracts for wheat and olives. In my data set about 30 per cent of strikes

negotiated collective contracts. Second, there was a large proportion of strikes of

unemployed workers or of workers demanding work (23 per cent). The general strike of

June 1934 concentrated 26 per cent of all strikes. Finally, there were several general

strikes organized by the National Confederation of Labour, which centred mostly in some

towns in Córdoba. For 16 per cent of strikes, I have not been able to trace the main

demand of the strike.

In order to analyse the number of strikes in each town I use a zero inflated poisson

model (although a negative binomial model does not deliver different results). Because of

the idiosyncatic nature of my data set, it is fair to argue that I might ge more zeroes than

expected, especially in isolated, small towns. Therefore the model first estimates a logit

regression to analyse the determinants of observing at least one event and then models

the count. In this case, the obvious candidate for the inflation effect on zeroes is population

(taken from the census). Therefore I estimate the following regressions for a group of 201

towns in Jaén, Córdoba and Sevilla (dataset excludes the capitals and Linares):

16

Strikes = a + b*ln (population in 1930) + c*ln(landinequality) + d*ln(popdensity) +

e*(dummy for a town between 250 and 500 meters above sea level) + f*dummy over 500

metres above sea level + g*dummy Jaén + h*dummy Sevilla

The regression model to a large extent is based on the historical and theoretical

discussion. Since labourers tended to concentrate in large towns, the coefficient of

population would capture among other things the insider power of “local” labourers in the

plains. The coefficient on land inequality is the response of workers to the inequality

effect. Finally, population density would capture the shock to local labour demand caused

by the prohibition to recruit temporary migrants. Dummies for altitude above sea level

capture the “hills effect” mentioned by Díaz del Moral and the dummies in each province

variations in the policies of prefects (the main authority at the provincial level).

Because population, land inequality and population density are highly collinear, I

also play with variations in the basic specification to evaluate the robustness of my

estimates. Table 4 gives the correlations and the descriptive statistics of the main

regressors:

Table 4. Correlation matrix population, land ownership inequality and population

density.. summarize lpop1930 llandinequality lpopdensity

Variable | Obs Mean Std. Dev. Min Max

-------------+--------------------------------------------------------

lpop1930 | 272 8.408768 .8579315 5.181784 10.30508

llandinequ~y | 208 3.415684 .8202427 .7030975 4.60517

lpopdensity | 265 -.5521035 .8904659 -2.980696 2.818398

. correlate lpop1930 llandinequality lpopdensity

(obs=208)

| lpop1930 llandi~y lpopde~y

-------------+---------------------------

lpop1930 | 1.0000

llandinequ~y | -0.1603 1.0000

lpopdensity | 0.3252 -0.4031 1.0000

17

In table 5 I present the results from the estimation:

Table 5. the determinants of strikes, 1931-1934

variables Zero inflated

poisson

All towns

Zero inflated

poisson,

Pop1930

excluded

Zero inflated

poisson,

Towns below

400 metres

Zero inflated

poisson, small

towns only

(below sample

mean)

Constant -2.23***

(0.645)

1.39***

(0.25)

-2.03***

(0.97)

1.66***

(0.39)

Ln (land in) 0.03

(0.07)

0.008

(0.065)

0.09

(0.12)

-0.07

(0.101)

Ln (popden) 0.09

(0.07)

0.22**

(0.07)

0.1

(0.1)

0.13

(0.11)

Ln (pop 1930) 0.39***

(0.06)

0.39***

(0.09)

Alt250500 -0.112

(0.13)

-0.18

(0.133)

-0.09

(0.16)

-0.63***

(0.21)

Altover500 -0.47***

(0.134)

-0.47***

(0.14)

-0.84***

(0.21)

Jaen 0.044

(0.12)

-0.03

(0.114)

0.07

(0.21)

0.07

(0.17)

Sevilla -0.73***

(0.134)

-0.8***

(0.134)

-0.86***

(0.16)

-1.04***

(0.2)

N 201 201 88 125

LR chi2 90.59 52.97 48.76 38.46

Prob>chi2 0.0000 0.0000 0.0000 0.0000

The results show how land inequality was irrelevant in the explanation of

strikes. The main predictor of strikes are the population of the town (remember

we are also correcting for the potential effect of population on the reporting of

strikes in newspapers), the altitude and the province (with Sevilla towns

18

organizing significantly less strikes). The negative coefficients on altitude and

Sevilla remain when I exclude the population variable or look only at sub-samples

of towns in my original data set. There are several potential reasons why

population might matter to explain the higher incidence of strikes. However, since

labourers tended to concentrate in large towns, the population effect, among other

potential causes, also reflects the insider power of the local labourers. On the other

hand, because large towns also had higher population densities part of this size

effect also is channelled through the shocks to local demand caused by the

municipal boundaries law.

In order to teasa out the various effects it is useful to consider only those

strikes that were organized demanding work. In this second exercise therefore I

only concentrate on the strikes organized by unemployed workers. Table 6 reports

the results from the regressions:

Table 6. Determinants of regressions demanding work.

Variables Zero inflated

Poisson regression

Zero inflated

Poisson regression

Lpop1930

excluded

Zero inflated

Poisson

regression, towns

below population

average

Constant -3.03***

(1.84)

-1.13***

(0.65)

-1.24

(1.04)

Ln (land in) 0.028

(0.15)

0.08

(0.144)

0.21

(0.24)

Ln (pop density) 0.36

(0.25)

0.46**

(0.23)

0.6**

(0.36)

Ln (pop1930) 0.214

(0.193)

Alt250500 -0.203

(0.4)

-0.32

(0.39)

-0.04

(0.7)

Altover 500 -1.46***

(0.68)

-0.9

(0.39)

-0.8

(0.7)

Jaén 2.35*** 2.34*** 1.79***

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(0.37) (0.38) (0.56)

Sevilla -1.46***

(0.678)

-1.54***

(0.68)

-1.7***

(0.86)

N 201 201 125

LR chi2 77.14 75.89 30.24

Prob >chi2 0.0000 0.0000 0.0000

In this case, the effect of population and altitutde still persist and Sevilla still

organizes far less strikes than the other two provinces. Jaén on the other hand

organized far more strikes of unemployed workers than any of the provinces. The

reason probably has to do with the harvest failure of olives in 1933. In this

regressions, the effect of population densities and local demand shocks is now an

important determinant of this type of strikes (although the predominance of Jaén

dwarfs any kind of other effect).

LAND INVASIONS

My second approximation to the levels of conflict uses cases of land invasions.

When looking at the qualititative evidence, it is clear land invasions in Andalucía

did not represent a threat to established property rights. Rather than squatting,

most invasions of property reflected the fact that workers started working in the

fields of some landowner or entered a large estate to pick up olives after harvest

(the so called “rebusca” done by old people and children) or to pick up acorns. To a

great extent, illegally entering the fields of a landowner to work responded to the

widespread use of the law of compulsory cultivation, a law passed by the

republican government forcing landowners to employ unemployed workers under

certain circumstances (when a commission could prove the property was not

being worked at the highest level of efficiency, but in fact there were surely many

cases of arbitrarily decided compulsory cultivation). Landowners and employers

bitterly complained about the workings of this law, which in fact left in the hands

of mayors (in many rural towns, socialist and pro-workers) and the so-called

“comisión de policía rural” (also controlled by mayors) the final decisions on the

decrees of compulsory cultivation.

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My data on land invasions still need substantial revisions, however I do not

think the picture is going to vary systematically. Graph 9 gives the histogram of

land invasions, which gives about 80 per cent of towns not reporting a single event

of workers trespassing a property. Indeed, several contemporary observers argued

that in fact the issue of land invasions was indeed an exageration of the right-wing

press. But even the moderate El Sol often ran a section called “Invasiones de fincas”

in which some cases of true workers’ trespassing were recorded along robberies

and other crimes.

Graph 9. Histogram of land invasions.0.2.4.6.8Fraction012345land invasionsAgain, I perform the same count model to understand the determinants of

invasions. Neither inequality or population density explain the results and as in the

other exercises population and the provincial dummies swallow all the

explanatory power. Quite surprisingly, land invasions did not decline in the hilly

areas, something not altogether surprising considering the type of property

trespassing and its reasons that we are considering. Results are presented in table

7:

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Table 7. Determinants of land invasions.

Variables Zero inflated

Poisson

Zero inflated

Poisson

Constant -5,93***

(2,13)

0,0145

(0,86)

Ln (land in) -0,11

(0,22)

0,011

(0,235)

Ln (popdensity) -0,33

(0,27)

-0,361

(0,29)

Ln(pop1930) 0,612***

(0,21)

Alt250500 -0,552

(0,367)

-0,42

(0,39)

Altover500 0,006

(0,382)

-0,028

(0,4)

Jaen -0,605

(0,44)

-0,804*

(0,454)

Sevilla 0,98***

(0,37)

0,72**

(0,4)

N 201 201

Chi2 29,66 20,01

Prob>chi2 0,0000 0,000

As in the case of strikes, and although I have to do some more work in my

data set of land invasions, the main determinants of invasions was again the

population of town. In this case, most probably most cases of property trespassing

were caused by workers anticipating a favourable concession from the mayor

forcing some landowner to employ unemployed workers. Provincial dummies

again seem to be crucial in determining land invasions, as workers in Sevilla were

clearly more prone to invade properties than in other provinces. Probably, one will

need to take a look at local politics to understand this effect.

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CONCLUSIONS

The picture that emerges from my study of rural conflict in Andalucía challenges

the view we have of the determinants of conflict. Firstly, conflict was more

concentrated than otherwise thought into few localities that concentrated a large

number of labourers. Conflict in this sense favoured local insider power at the

expense of workers in other towns, and therefore could not be generated by

widespread harvest failure. When I look at the determinants of strikes demanding

work, I show how probably shocks to the local demand of labour caused by the law

of municipal boundaries were important, although harvest failure in olives in Jaén

also increased the strikes of unemployed workers in winter. My first preliminary

results on land invasions suggests this was a phenomenon that also required local,

union power and favoured the local, permanent labourers in the large towns of the

plains.

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