Economic Growth from Broadband Penetration, and implications on the National Broadband Plan.

Theeradej Suabtrirat, Texas Tech University.

Presentation for Southern Economic Association 84th Annual Meeting.

November 24th, 2014. 3.00-4.45pm. Session 17M.

Let’s see how important the internet is for our today’s lives.

Credit: http://joyreactor.com/post/477777

No internet is not a big problem. But the slow oneis.

Credit: http://wanna-joke.com/slow-internet/

An internet connection is not free at a Marriott hotel?

Broadband Penetration• Broadband Penetration is the

proportion of an internet access that is classified as high-speedinternet.

• It generates two forms of return to our economy.

• Economic Growth (Tangible return)

• Welfare Improvement (Non-Tangible return)

Two forms of return• Economic Growth (Tangible return)

• An increase in Gross Domestic Product (GDP) from using the internet as a trading platform.

• Firms do an e-commerce with each other by networking technology.

• Households in a small city buy goods not available locally. Or they may do a showrooming: visit a local store but buy cheaper online.

Two forms of return• Economic growth measured by GDP may

not reflect the total impact of broadband penetration, since the large proportion of it is not reflected as monetary transactions.

• Welfare Improvement (Non-tangible return)

• A mother can read medical article and video to find a way to cure her daughter's cancer. She says “You cannot put a price on that.” (The Economist, 2013).

• Online content substitutes printed media, which may reduce market transactions or GDP.

Credit: The Economist: http://www.economist.com/news/finance-and-economics/21573091-how-quantify-gains-internet-has-brought-consumers-net-benefits

The National Broadband Plan• The plan aims to create a high-

performance America

• broadband is affordable everywhere. Low price encourages households adoption.

• everyone has a computer skillto take advantage of high-speed internet.

The National Broadband Plan• The plan’s current target is 4

Mbps for download speed and at least 1 Mbps for upload speed.

• The plan wants 100% of American household to have an internet in their home.

• However, this target is very difficult to reach since the cost of providing a connection to low-density area is prohibitively expensive. (See next slide)

The National Broadband Plan

• Marginal cost of serving 95th -100th of households is disproportionate.

• To serve 100% of American household, $24 billion public funding is needed. Since private internet provider companies find unprofitable to operate in low-density areas.

Broadband Availability Gap, by percent of U.S.housing units served.

Source: Federal Communication Commission, 2014.

Scope of this paper• This paper estimates the

effect of broadband penetration on output growth to the United States using 2000-2011 state-level data.

• This paper estimates average effect from the mentioned eleven-year period, and do not evaluatethe return on investment from reaching 100% penetration of the national broadband plan.

The figure shows that the broadband adoption rate starts at 4% in 2000 and increases to 68% in 2011 (Source: NTIA, 2014).

Contribution of this paper• To my knowledge, there are only two authors who study the

effect of broadband penetration on output growth in the United States.

• I do not have an intention to discredit their work. I simply would like to show how my work extends their result.

• Crandall et.al. (2007) uses cross-sectional regression to estimate the effects of broadband penetration on output over the 2003-2005 period (vs. my work is from 2000-2011 period).

• They find an insignificant positive relationship; an increase in broadband line of 0.01 lines per capita raises private non-farm GDP growth increases by 0.16 percent (vs. my work find a significant positive relationship in some models).

Contribution of this paper• Thompson and Garbacz (2008) estimates the direct and the

indirect economic impact of broadband penetration using US state-level data for 2001-2006 (vs. my work is from 2000-2011 period).

• They find a small positive or even a significant negative impact associated with broadband penetration. I try to imitate my model to his to verify the existence of a negative relationship but finally find a positive one.

Empirical Framework• The empirical framework of broadband penetration on economic

growth is in line with those of Thompson and Garbacz (2008), Qianget.al. (2009), and Koutroumpis (2009).

• GSPcap = f(BBpen, LFP, EduH, GOScap, Tax).

• GSPcap Gross state product per capita

• BBpen Broadband penetration

• LFP Labor force participation

• EduH Proportion of state’s residents whose education is

high school or better

• GOScap Gross operating surplus per capita

• Tax Tax and state-local tax burden

Variables Definition

BEA Bureau of Economic Analysis. FCC Federal Communications Commission.BLS Bureau of Labor Statistics. ACS American Community Survey.CPS Current Population Survey.

Variables Definition Source

GSPcap Gross state product per capita in year 2000 dollars.

Original value (Chain year 2009 dollars) is deflated by Consumer

Price Index.

BEA

BBpenBroadband penetration =

Residential BBL + Commercial BBLPopulation

A broadband line (BBL) is an internet connection with speed over

200 kbps in at least one direction. Note: BBpen may exceed 1.00.

FCC

LFP Labor Force Participation. BLS

EduH Proportion of state’s residents whose education is high school

education or better.

ACS & CPS

GOScap Gross operating surplus by state per capita in year 2000 dollars.

Original value (Chain year 2009 dollars) is deflated by Consumer

Price Index.

BEA

Tax State local tax burden

= PerCapitaTaxPaidtoOwnState+PerCapitaTaxPaidtoOtherState

per capita income

Tax

Foundation

Acronym

Two Modeling Approaches1. Cross-sectional regression of variables’

growth.

• The Traditional Approach.

2. Panel Data Model.• The more successful technique as reported by

Previous literature (Katz 2012).

Cross-Sectional Growth Equation

• GSPcap_Gr = β0 + β1*GSPcap2000_Log + β2*BBpen_Gr + β3*LFP_Gr + β4*EduH_Gr + β5*GOScap_Gr + β6*Tax_Gr + 𝜶𝒊 𝑹𝒊 + e

• The suffix _Gr represents compound annual growth rate (CAGR), computed as:

• CAGR = 𝐸𝑛𝑑𝑖𝑛𝑔 𝑉𝑎𝑙𝑢𝑒

𝑆𝑡𝑎𝑟𝑡𝑖𝑛𝑔 𝑉𝑎𝑙𝑢𝑒

1

𝑁𝑜 𝑜𝑓 𝑌𝑒𝑎𝑟𝑠 – 1.

• Example: GSPcap_Gr = 𝐺𝑆𝑃𝑐𝑎𝑝2011

𝐺𝑆𝑃𝑐𝑎𝑝2000

1

11 – 1, BBpen_Gr = 𝐵𝐵𝑝𝑒𝑛2011

𝐵𝐵𝑝𝑒𝑛2000

1

11 - 1

• GSPcap2000_Log refers to the natural log of initial GSPcap year 2000.

• Ri represents dummies for nine U.S. regions according to U.S. Census’s definition. Region 9 (Pacific Division) is dropped.

Cross-Sectional Growth Equation using laggedindependent variables

• GSPcap_Gr = β0 + β1*GSPcap2000_Log + β2*BBpen_GrLag+ β3*LFP_GrLag + β4*EduH_GrLag

+ β5*GOScap_GrLag + β6*Tax_GrLag

+ 𝜶𝒊 𝑹𝒊 + e

• The suffix _GrLag represents compound annual growth rate but the ending value and starting value are lagged one year before dependent variable,

computed as: For example, BBpen_GrLag = 𝐵𝐵𝑝𝑒𝑛2010

𝐵𝐵𝑝𝑒𝑛2000

1

11 - 1

• This model use lagged value as explanatory variables to avoid simultaneity bias.

• GSPcap_Gr is one year ahead to that of X_GrLag.

• CAGR = 𝐸𝑛𝑑𝑖𝑛𝑔 𝑉𝑎𝑙𝑢𝑒

𝑆𝑡𝑎𝑟𝑡𝑖𝑛𝑔 𝑉𝑎𝑙𝑢𝑒

1

𝑁𝑜 𝑜𝑓 𝑌𝑒𝑎𝑟𝑠 – 1. Example: GSPcap_Gr = 𝐺𝑆𝑃𝑐𝑎𝑝2011

𝐺𝑆𝑃𝑐𝑎𝑝2001

1

11 – 1.

Cross-Sectional Growth Equation • Both models have

correct signs.• Positive sign for

BBpen_Gr, LFP_Gr, EduH_Gr, and GOScap_Gr.

• Negative sign for GSPcap2000_Log and Tax_Gr.

• However, the coefficient for BBpen_Gr is insignificant for both models.

Note: T-statistics are in parenthesis.* Statistically significant at 10%** Statistically significant at 5% ** Statistically significant at 1%

Model (3.2) Model (3.2 Lag)

CAGR method

Y:2000-2011,

X's:2000-2011

CAGR method

Y:2001-2011,

X's:2000-2010

Intercept 0.0153 0.0500

(0.53) (1.67)

GSPcap2000_Log -0.0021 -0.0051 *

(-0.80) (-1.87)

BBpen_Gr 0.0088 0.0081

(0.99) (0.93)

LFP_Gr 0.6499 ** 0.4534 *

(2.27) (1.71)

EduH_Gr 0.1437 0.3089

(0.37) (0.84)

GOScap_Gr 0.4335 *** 0.3636 ***

6.24 (5.02)

Tax_Gr -0.1829 -0.1386 *

(-2.05) (-1.75)

Regional Dummies Included Included

Adjusted R-square 0.8319 0.7681

Independent Variables

Estimated Economic Growth From Cross-Sectional Growth Model.• Overview:

• Detailed Result (Open for discussion at the end of the presentation)

• From cross sectional growth estimate of model (3.2 Lag) and a complex calculation, an average increase (CAGR population weighted) of 0.36 unit of broadband penetration (from year 2000 to 2010) contributes to an increase of 30 billion dollars (in constant year 2000) of U.S. GDP per year. This number is about 0.27% of $11 trillion dollar, the average (over 2001 to 2011) US GDP deflated to constant year 2000 dollar.

• Note: BBpen = NoOfBBLine/Population. It may exceed 1.00.

An average increase of 0.36 unit of

BBpen per year

An average increase of $30 billion of U.S. GDP per year

This number is about 0.27% of

average U.S. GDP ($11 trillion)

Panel Data Model• Basic Panel Data Model:

• GSPcap_Logit = β0 + β1*BBpen_Logit + β2*LFP_Logit

+ β4*EduH_Logit + β5*GOScap_Logit + β6*Tax_Logit

+ 𝛼𝑖 𝑆𝑖 + 𝛿𝑡 𝑇𝑡 + e

• The suffix _Log represents natural log imposed on variables.

• Si represents state dummies for fifty U.S. states and Washington DC (i.e. S=11) according to U.S. Census’s definition.

• Tt represents time dummies for year 2000 to 2011.

Panel Data Model• Panel Data Model with Interaction Terms

• GSPcap_Logit = β0 + (γ1*BBpenHigh + γ2*BBpenMed +

γ3*BBpenLow)*BBpen_Logit

+ β2*LFP_Logit + β4*EduH_Logit + β5*GOScap_Logit

+ β6*Tax_Logit + 𝛼𝑖 𝑆𝑖 + 𝛿𝑡 𝑇𝑡 + e

• Interaction terms are added.

• BBpenHigh, BBpenMed, BBpenLow are zero or one dummies.

• States, whose average broadband penetration over 2000-2011 is 66th to 99th percentile, 33th to 65th percentile, and 1th to 32th

percentile of the U.S broadband penetration, falls into the group of BBpenHigh, BBpenMed, BBpenLow respectively.

Panel Data ModelStates grouping based on average broadband penetration over 2000-2011.

Panel Data Model• Panel Data Model with Interaction Terms and Lagged variables.

• GSPcap_Logit = β0 + (γ1*BBpenHigh + γ2*BBpenMed +

γ3*BBpenLow)*BBpen_LogLagit

+ β2*LFP_LogLagit + β4*EduH_LogLagit

+ β5*GOScap_LogLagit

+ β6*Tax_LogLagit + 𝛼𝑖 𝑆𝑖 + 𝛿𝑡 𝑇𝑡 + e

• The suffix _LogLag represents the natural log on variables that is lagged one year before that of dependent variables.

• For example, GSPcap_Log of year 2011 is regressed on BBpen_Log of year 2010.

Panel Data Model

Note: T-statistics are in parenthesis.* Statistically significant at 10%** Statistically significant at 5% ** Statistically significant at 1%

• For Model (3.6), BBpen_Log coefficient is positive but insignificant.

• For Model (3.7), three BBpen interaction terms are all significant.

• For Model (3.7) Lag, only one of the three BBpeninteraction term is significant. And T-statistics are smaller than that of Model (3.7).

Dependent variable: GSPcap_Ln for Model (3.6), (3.7), and (3.7) Lag

Model (3.7) LagRegress Y=2001 on

X's=2000 and

Y=2011 on X's=2010

Intercept 4.9551 *** 5.0213 *** 5.424 ***

(12.17) (12.29) (10.79)

BBpen_Log 0.0060 N/A N/A

(1.46)

Bbpen_High N/A 0.0137 *** 0.0110 *

(2.63) (1.75)

Bbpen_Med N/A 0.0076 * 0.0070

(1.66) (1.29)

Bbpen_Low N/A 0.0091 ** 0.0081

(2.15) (1.60)

LFP_Log 0.3745 *** 0.3441 *** 0.2365 ***

(5.76) (5.19) (2.86)

EduH_Log 0.0823 0.0885 0.1887 **

(1.19) (1.29) (2.31)

GOScap_Log 0.3924 *** 0.3961 *** 0.3522 ***

(29.07) (29.37) (20.87)

Tax_Log -0.0260 -0.0285 0.0083

(-1.07) (-1.14) (0.26)

State Dummies Included Included Included

Time Dummies Included Included Included

Adjusted R-square 0.9927 0.9928 0.9901

Variables Model (3.6) Model (3.7)

Panel data with FE Panel data with FE

and interaction

Estimated Economic Growth From Panel Data Model.• Overview:

• Detailed Result (Open for discussion at the end of the presentation)

• From panel data estimate of model (3.2 Lag) and a complex calculation, an average increase (CAGR population weighted) of 0.36 unit of broadband penetration (from year 2000 to 2010) contributes to an increase of 33 billion dollars (in constant year 2000) of U.S. GDP per year. This number is about 0.29% of $11 trillion dollar, the average (over 2001 to 2011) US GDP deflated to constant year 2000 dollar.

• Note: BBpen = NoOfBBLine/Population. It may exceed 1.00.

An average increase of 0.36 unit of

BBpen per year

An average increase of $33 billion of U.S. GDP per year

This number is about 0.29% of

average U.S. GDP ($11 trillion)

Panel Data Model: Result Comparison• Overview: The impact of broadband on economic growth varies for different

level of broadband penetration. From low to medium to high BBpen, Koutroumpis (2009) finds an upward sloping curve, while this paper finds a U-shape curve.

• Finding Details: (Open for discussion at the end of the presentation)• Koutroumpis (2009) studies the contribution of broadband to economic growth of OECD countries for 2002-

2007 and finds that the such impact increases with penetration level like an upward sloping curve. Note:DepVar:Log(GDP in million $). IndepVar:broadband penetration is per 100 inhibitants. Unit is in percentage.

• On the contrary, this study indicates that such impact looks like a U-shape curve. Note: DepVar:Log(GSPcap2000 $). IndepVar:Broadband penetration = No. of broadband lines / Population. (Mean=0.26, Max=1.90).

• Note: Coefficient size of BBpen is not quantitatively comparable since variables are defined differently.