Government Size and Economic Growth: A new Framework and Some Evidence from Cross-Section and Time-Series Data

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1 1 Government Size and Economic Growth: A new Framework and Some Evidence from Cross-Section and Time-Series Data Original Paper by Rati Ram (1986) Replication and Extension by Nicolas Lopez ECON 5341 The University of Texas at Arlington

2 2 Economic Question What is the impact of government size in economic growth? There is limited and contradicting literature in the topic. Rubinson (1977) case for positive Landau (1983) case for negative It is a controversial topic since it is subject to political debate. We will not focus on the politics of the matter.

3 3 Purpose Try to predict the total effect of government size on economic growth. Does a bigger government promote growth or does it hinders growth? The externality effect of government on the economy. How does the government sector affects the private sector? Sector productivity differentials. In which sector there is higher input productivity?

4 4 Goals Develop a model that allows us to answer the questions stated previously. Add Cross-Section and Time-Series data to our model to empirically answer the questions. Compare the results with different set of countries.

5 5 Theoretical Framework 2-sector production function proposed by Feder (1983). Let s assume an economy with 2 sectors: Government Sector (GG) Non-Government Sector (CC) Such that YY = CC + GG (3c)

6 6 Also lets assume that each sector is made up of two components: Labor (LL) and Capital (K) Including a measure for the externality of government we will say that: CC = CC(LL cc, KK cc, GG) (1) GG = GG LL gg, KK gg (2) We also know that LL = LL cc + LL gg (3a) KK = KK cc + KK gg (3b)

7 7 We will need a specification that allow us to determine the relative factor productivity GG LL CC = LL KK CC = 1 + δδ (4) KK The sign of δ determines which sector has higher factor productivity. If δ is positive we will know that there is higher productivity in the government sector.

8 8 Derivation of the Equations Using equations (1) to (3) we know that By definition Thus CC = CC LL LL cc + CC KK II CC + CC GG GG GG = GG LL LL gg + GG KK II gg YY = CC + YY = CC LL LL cc + CC KK II CC + CC GG GG + GG LL LL gg + GG KK II gg YY = CC LL LL cc + CC KK II CC + CC GG GG + CC LL (1 + δδ) LL gg + CC KK (1 + δδ)ii gg YY = CC LL LL cc + LL gg + CC KK (II cc +II gg ) + CC GG GG + δδ(cc LL LL gg + CC KK II gg ) GG

9 9 Aside CC LL LL gg + CC KK II gg = 1 1+δδ GG LL LL gg + GG KK II gg = GG 1 + δδ Also from (3) LL gg II gg LL LL cc + II II cc + YY = CC LL LL + CC KK II + CC GG GG + δδ( YY = CC LL LL + CC KK II + GG(CC GG + GG 1+δδ ) δδ 1+δδ )

10 10 From Bruno (1968), we know that CC LL = ββ YY LL that CC KK = αα We will also divide everything through by YY YY YY = αα II YY + ββ LL LL + δδ 1 + δδ + CC GG GG GG GG YY and We can show that if we adopt a possible specification that government affects consumption with constant elasticity such that: CC = CC LL cc, KK cc, GG = GG θθ ψψ(ll gg, KK gg ) And we can show that CC GG CC GG = θθ CC CC GG = θθ YY GG = θθ 1 GG YY = θθ θθ GG YY GG YY YY

11 11 Returning to our original equation, we can substitute for CC GG YY = αα II YY + ββ δδ LL + Simplifying we get Equation 5 YY = αα II + ββ LL + YY 1 + δδ + θθ θθ GG YY δδ 1+δδ θθ If we impose the restriction that δδ 1+δδ Equation 6 YY = αα II YY + ββ LL + θθgg If we don t substitute for CC GG we get Equation 7 YY = αα II YY + ββ LL + (δδ CC GG ) GG GG GG YY GG GG + θθ GG YY = θθ we get GG YY

12 12 Equation 5 Using equations 3 and 4 we are able to get Equation 5 YY = αα II + ββ LL + YY δδ 1+δδ θθ GG GG + θθ GG YY αα Marginal product of capital in C ββ Elasticity of non-government output w.r.t L δδ Intersectoral productivity differential θθ elasticity of the marginal externality effect (the percentage increase in C when G increases by 1 percent)

13 13 Equation 6 If we allow for δδ 1+δδ = δδδ = θθ we will get Equation 6 YY = αα II + ββ LL + θθgg YY θθ externality effect of government Since we are imposing the restriction we will be able to calculate δδ, based on δδδ = θθ, from Equation 6

14 14 Equation 7 We can also derive Equation 7 if we prefer to calculate CC GG YY = αα II + ββ LL + (δδ CC YY GG ) GG GG YY (δδ CC GG ) overall effect of government size CC GG marginal product (increase in C, for constant K and L as G increases by one unit) The benefit of this equation is that it does not have the collinearity that might occur in Equation 5 or the restriction imposed in Equation 6

15 15 Objective We want to determine the direction of the overall effect of government on growth Focus on the coefficient δδ CC GG in Equation 7 Called govef in the output We also want the direction of the externality effect We get this from the estimate from the coefficient (θθ) in Equation 6 Called govg in the output We might also get the externality and the intersectoral differential We get these from Equation 5

16 16 Data For our estimates we will use the data compiled from the Penn World Tables (167 countries) From 1960 to 1980 for the replication From 1980 to 2011 for the extension We need: YY GDP in international dollars GG YY & II YY share of government expenditures and investment of total GDP LL we will use population growth as a proxy for labor

17 17 Cross-Sections We will divide our data by decade in order to control for structural breaks Except in the last decade in which 2011 is included. We will use the mean value for the share of government ( GG YY) and share of investment ( II YY). For the other variables we fit an exponential trend to approximate the growth rate in the decade.

18 to 1970 Table 1: Cross Sectional Results 1960 to 1970 (1) Paper (2) Paper (3) Paper VARIABLES Equation 5 Equation 6 Equation 7 csh_i *** 0.114*** *** 0.114*** 0.100*** 0.118*** popg *** *** *** govef 0.510* *** 1.286*** govg * 0.199** 0.226*** Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 Observations R-squared Non-significance/marginal significance of govef and govg in Equation 5 Positive and significant coefficient in govg in Equation 6 Externality effect of government is positive Positive and significant coefficient of govef in Equation 7 Total effect of Government in growth is positive

19 to 1980 Table 2: Cross Sectional Results 1970 to 1980 (1) Paper (2) Paper (3) Paper VARIABLES Equation 5 Equation 6 Equation 7 csh_i *** 0.097*** *** 0.100*** *** 0.119*** popg 0.360** 0.453* 0.360** *** govef *** 1.744*** govg 0.415*** 0.485*** 0.420*** 0.384*** Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 Observations R-squared Non-significance of govef and significance of govg Equation 5 Positive and significant coefficient in govg in Equation 6 Externality effect of government is positive Positive and significant coefficient of govef in Equation 7 Total effect of Government in growth is positive

20 to 1990 Table 3: Cross Sectional Results 1980 to 1990 (1) (2) (3) VARIABLES Equation 5 Equation 6 Equation 7 csh_i popg * ** govef *** govg 0.320*** 0.392*** Observations R-squared Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 Similar results to what we have seen before Non-significance of govef and significance of govg, makes us prefer Equation 6 Positive and significant coefficient in govg in Equation 6 Externality effect of government is positive Positive and significant coefficient of govef in Equation 7 Total effect of Government in growth is positive

21 to 2000 Table 4: Cross Sectional Results 1990 to 2000 (1) (2) (3) VARIABLES Equation 5 Equation 6 Equation 7 csh_i ** ** ** popg 0.752*** 0.833*** 0.752*** govef 1.595*** 1.782*** govg *** Observations R-squared Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 Something interesting happened during this decade In Equation 5 we see that the coefficient of govg to be insignificant, while govef is significant. Indicates that δ might be negative Equation 6 does not work this time as θθ δδ Equation 7 still tells us that the overall effect of government is positive.

22 to 2011 Table 5: Cross Sectional Results 2000 to 2011 (1) (2) (3) VARIABLES Equation 5 Equation 6 Equation 7 csh_i popg 0.577*** 0.595*** 1.000*** govef *** govg 0.491*** 0.445*** Return to the same pattern that we had before Similar conclusions can be reached Observations R-squared Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

23 23 Cross-Section Results Eq. 5 Eq. 6 Eq. 7 govef govg govg govef * ** 0.693*** *** 0.420*** 1.338*** *** 0.392*** 1.372*** *** *** 1.782*** *** 0.445*** 1.141*** Results are very consistent per decade except for the 90 s, especially if we focus in Equation 5. In all other cases as the restriction applied on makes sense, we can use Equation 6 to determine the directional of the externality. Concluding that the externality is positive and that the factor productivity is positive as well.

24 24 Time-Series Take advantage of the Penn World Tables to conduct a time-series estimate each country. There are some benefits of time-series over crosssectional. Since there are limited number of observations we should be careful with the results (especially for those with 21 obs.) We will run the three equations for the each individual country, using all the observations available (min. 21). We will use the difference of the logs to generate the growth rates that will be used in the estimations.

25 25 Individual Time-Series Output* Eq. 6 Eq.7 Eq. 6 Eq.7 Eq. 6 Eq.7 1 Angola 0.181*** 0.436*** 31 China 0.608*** 2.916*** 61 Guinea-Bissau 0.255*** 0.749*** 2 Albania Côte d'ivoire 0.429*** 2.509*** 62 Equatorial Guinea 0.446*** 0.668** 3 Argentina 0.191*** 1.641*** 33 Cameroon 0.242*** 1.004*** 63 Greece 0.223** 1.277** 4 Armenia Congo 0.352*** 0.975** 68 Croatia 0.437*** 1.649*** 7 Austria 0.247*** 1.769*** 36 Colombia Hungary 0.417*** 1.463*** 9 Burundi 0.251*** 1.036*** 37 Comoros 0.286*** 0.902*** 70 Indonesia Belgium 0.321*** 1.773*** 39 Costa Rica 0.337*** 2.267*** 71 India 0.174** 1.245*** 13 Bangladesh 0.144*** 0.949*** 40 Cyprus Ireland 0.368*** 1.739** 14 Bulgaria 0.217*** 0.504*** 41 Czech Republic 0.408** 1.538*** 73 Iran 0.463*** 2.544*** 15 Bahrain 1.135*** 6.617*** 42 Germany Iceland 0.363** 1.908** 17 Bosnia and Herzegovina 0.864*** 2.750*** 45 Denmark Israel Belarus Ecuador 0.216** 0.815** 77 Italy 0.384*** 2.436*** 20Bermuda Spain 0.464*** 2.481*** 79 Jordan 0.462*** 0.925*** 21Bolivia 0.317*** 1.348*** 50Estonia Japan 0.530*** 3.407*** 22Brazil 0.274*** 1.115*** 51Ethiopia 0.189*** 1.252*** 81Kazakhstan 0.661** 2.808** 26Botswana Finland 0.400*** 1.898** 83Kyrgyzstan 0.558*** 1.590*** 27Central African Republic 0.157*** 1.142*** 53Fiji 0.406*** 1.915*** 84Cambodia 0.122** Canada France 0.387*** 2.043*** 85Saint Kitts and Nevis 0.310* 0.778* 29Switzerland United Kingdom 0.236*** 1.047** 86Republic of Korea 0.549*** 3.686*** 30 Chile 0.513*** 2.614*** 57 Georgia 0.353*** 1.390*** 87 Kuwait Results reported if the regression was significant 116 countries out of 167

26 26 Eq. 6 Eq.7 Eq. 6 Eq.7 Eq. 6 Eq.7 88 Lao 0.290*** 1.153*** 118 Nepal 0.246*** 1.055*** 148 Thailand 0.433*** 1.959*** 89 Lebanon 0.660*** 2.480*** 119 New Zealand Tajikistan 0.674** 1.571*** 90 Liberia 0.371*** 3.131*** 121 Pakistan *** 0.393*** 150 Turkmenistan 0.264*** 0.685** 91 Saint Lucia 0.948*** 2.255*** 122 Panama 0.310*** 1.571*** 152 Tunisia 0.228** 1.132** 92 Sri Lanka 0.215*** 0.863*** 123 Peru 0.320*** 1.622*** 153 Turkey 0.303*** 2.387*** 94 Lithuania 0.568*** 1.960*** 124 Philippines 0.398*** 2.119*** 154 Taiwan 0.260* 1.187* 98 Morocco 0.168*** 0.582*** 125 Poland 0.552*** 2.327*** 155 Tanzania 0.443*** 0.890*** 99 Moldova 0.423*** 1.243*** 126 Portugal 0.256*** 1.575** 156 Uganda 0.361*** 2.775*** 102 Mexico Paraguay 0.147** 1.137** 157 Ukraine 1.081*** 3.114*** 104 Mali 0.172*** 0.723*** 129 Romania 0.159*** 0.829*** 158 Uruguay 0.315*** 1.756*** 105 Malta 0.790** 3.541* 130 Russia 1.090*** 4.021*** 159 United States Montenegro 0.829*** 2.521*** 131 Rwanda 0.415*** 1.462*** 160 Uzbekistan 0.641*** 1.211*** 107 Mongolia 0.186*** 0.726*** 134 Senegal 0.270*** 1.206*** 161 St. Vincent 0.409*** 0.970*** 108 Mozambique 0.109** 1.756** 136 Sierra Leone 0.297*** 1.266*** 163 Viet Nam 0.419** 2.267* 109 Mauritania El Salvador ** 166 Zambia 0.225*** 0.859*** 110 Mauritius 0.778*** 3.489*** 138 Serbia 0.969*** 3.295*** 167 Zimbabwe Malawi 0.282*** 1.272** 140 Suriname 0.168*** 0.710** 114 Niger 0.397*** 1.429*** 141 Slovakia 0.422** 1.421** 115 Nigeria 0.315*** 2.048*** 145 Syria 0.555*** 1.741*** 116 Netherlands Chad 0.759*** 1.184***

27 27 Summary of Time-Series Paper Results Entire Sample Eq. 6 Eq. 7 Eq. 6 Eq. 7 Positive Coefficients, significant at the 1 percent level Positive Coefficients, significant at the 5 percent level Positive Coefficients, significant at the 10 percent level Positive Coefficients, not significant even at the 10 percent level Total Negative Coefficients, significant at the 1 percent level Negative Coefficeints, significant at the 5 percent level Negative Coefficeints, significant at the 10 percent level Negative Coefficients, not significant even at the 10 percent level Total Total Sample Size

28 28 Limited Sample Paper Results Limited Sample Eq. 6 Eq. 7 Eq. 6 Eq. 7 Positive Coefficients, significant at the 1 percent level Positive Coefficients, significant at the 5 percent level Positive Coefficients, significant at the 10 percent level Positive Coefficients, not significant even at the 10 percent level Total Negative Coefficients, significant at the 1 percent level Negative Coefficients, significant at the 5 percent level Negative Coefficients, significant at the 10 percent level Negative Coefficients, not significant even at the 10 percent level Total Total Sample Size

29 29 Time-Series Results We see that in the majority of the countries the externality effect of government is positive Significantly positive (74%) and positive in (92%) of the cases. Likewise, the overall effect of government is positive in the majority of the cases. Positive in (90%) of the cases and significantly positive in (70%). Even more overwhelming if we only consider the cases in which the regression is statistically significant.

30 30 Time-Series Results The Time-Series results are congruent with the Cross-Sectional results that were discussed earlier. Positive externality and positive total effect of government in the economy. One of the questions that arise is if the size of the economy and the income level has an effect on whether or the results above.

31 31 OECD Countries vs. LDC Countries OECD LDC Eq. 6 Eq. 7 Eq. 6 Eq. 7 Positive Coefficients, significant at the 1 percent level Positive Coefficients, significant at the 5 percent level Positive Coefficients, significant at the 10 percent level Positive Coefficients, not significant even at the 10 percent level Total Negative Coefficients, significant at the 1 percent level Negative Coefficeints, significant at the 5 percent level Negative Coefficeints, significant at the 10 percent level Negative Coefficients, not significant even at the 10 percent level Total Total Sample Size

32 32 We see that there is no clear difference in the effect of government size on the economy among the poor countries and the rich countries. This rises more questions than what answers.

33 33 Conclusion We developed a model that allows us to estimate the externality effect of government, the sector factor productivity and the overall effect of government. We get consistent results for the five decades in the Cross-Section which is supported by the Time-Series results.

34 34 From Equation 6 we were able to figure out the marginal externality effect of government size on the economy. Which is positive in the majority of cases in the Time-Series and Cross-Sections. From Equation 7 we determined the sign of the overall effect of government size Again, it is positive in the majority of cases in the Time-Series and Cross-Sections. Even extending the data for thirty additional years, the conclusions are consistent with those reached in the original research.

35 35 Call for Caution Further questions Although there are some consistent results in the sign of the externality, the overall effect and the intersectoral productivity differential, it might be erroneous to use the magnitudes. There might be a problem of simultaneity that is not being addressed in the model. Does the economy grows because the government size increases or does government size increases because the economy is growing?

36 36 Is the effect of government size linear? Does the size of the government reaches a point that starts to hinder growth? We are not including trade or taxes directly into our model, if we controlled for them does the result changes?

37 37 Questions?

Supplementary Appendix for. Version: February 3, 2014

Supplementary Appendix for. Version: February 3, 2014 Supplementary Appendix for When Do Governments Resort to Election Violence? Version: February 3, 2014 This appendix provides supplementary information not included in the published draft. Supplementary