Catholic University of Eastern Africa, Nairobi, Kenya University of Dar-es-Salaam, Tanzania Kenyatta University, Nairobi, Kenya Makerere University, Kampala, Uganda Saint Augustine University of Tanzania, Mwanza University of Nairobi, Kenya Sokoine University of Agriculture, Morogoro, Tanzania Uganda Martyrs University, Nkozi, Uganda University of Zambia, Lusaka University of Zimbabwe, Harare
 

 

DETERMINANTS OF ECONOMIC GROWTH

A PANEL DATA OF 60 COUNTRIES

Thomas Mwebaze

March 2002

 

Introduction

This paper is based on the study by William Easterly and Sergio Rebelo; Fiscal policy and Economic growth, an empirical investigation. The study is an extension of the work by Robert Barro. We use a panel of annual data for 60 countries from 1960 to 1996 instead of a cross section data.

Easterly and Rebelo state that fiscal policy is an important growth determinant.

In their study, using cross section data of 100 countries, Easterly and Rebelo came up

with the following findings;

- Government consumption is robustly correlated with growth

- Government revenue is also consistently correlated with growth and private investment.

- That tax revenue has a negative impact on growth.
 
- Higher income countries have relatively higher government health expenditure and
 
   larger social security programs.
 
- Poor countries have high debt burden, which affects their rate of growth.

According to Easterly and Rebelo, high levels of inequality in income distribution observed prior to 1970 were associated with higher levels of publicly provided education in the period from 1970 –1988. They also come to a conclusion that high public spending on infrastructure investment raises growth.

The results of Easterly and Rebolo are presented in table 1 and 2 below.

Table 1.      
Regression with per capita GDP growth rate as a dependent variable  



 
Independent Variable Coeffient  



 
Constant   0.01  
    (1.19)  
       
Primary enrollment 0.0247  
    (2.24)  
       
Secondary enrollment 0.0439  
    (2.09)  
       
Marginal tax rate with respect to GDP -0.064  
    (-2.04)  

The t-statistics are given in parentheses.

Table 2.

Partial Correlation between fiscal aggregates and Growth

Fiscal Variable Basic Regression  


 
   Government Surplus/GDP 0.142  
  (3.13)  
     
Government Consumption/GDP -0.098  
  (-2.68)  
     
   Government Revenue/ GDP 1.584  
  (5.36)  
     
Expenditure on general public service/GDP -0.236  
  (-3.38)  
     
Marginal tax rate -0.064  
  (-2.04)  
 
 

The coefficients reported in table 2 above are all significant.

Literature Review

Empirical findings of Barro Robert J in August 1990 strongly support the general notion of conditional convergence. That for given starting level of real per capita GDP, the growth rate is enhanced by higher initial schooling and life expectancy, lower fertility, lower government consumption, better maintenance of rule of law, low inflation and improvement in the terms of trade. For given values of these and other variables, growth is negatively related to the initial level of real per capita GDP. Political freedom has only a weak effect on growth but there is some indication of a non-linear relation.

In the initial phase, growth in developing countries is hindered primarily owing to the lack of the basic economic foundations in the shape of the growth of environmental facilities and services. Their growth demands considerable investments in social and economic overheads. This is the initial phase of the process of development where the government of an under developed country is required to create the basic economic foundation for development by direct investment in social and economic overheads

According to Barro, higher initial per capita GDP is substantially negatively related to subsequent per capita growth. Per capita growth is positively related to the proxies for the initial human capital, holding fixed GDP60 and the other variables.

The idea that government policy is important in shaping the growth process has been a recurrent theme of the development literature for the past three decades (see for instance Krueger (1978) and Chenery (1986)). Growth theorists have also shared the interest in the role of public policy and the neoclassical growth model of Solow (1956) has been used as a testing ground to study the dynamic effects of numerous policies.

Under the revolutionary impact of Keynes’ book published in 1936, professional economists shifted their interest to an aggregate analysis of the economy. Keynes’ theory of national income and employment emphasized the fact that government’s fiscal operations could be administered so as to influence the level of income and employment. In addition to the aim of securing collective consumption, taxes could be imposed to curtail effect ive demand, and expenditure could be incurred in order to increase investment, income, and employment. Compensatory financing was placed at the core of the new macroeconomics. The budgetary weapons –taxes, borrowing and expenditure, -were analysed in the light of their effectiveness in promoting full employment with stable prices. In this way, the modern concept of fiscal policy as an instrument of economic growth, emerged.

The Keynesian exposition was a short-run analysis of the capital formation process. It took account of the income –increasing effects of investment. Later developments saw a shift from the Keynesian short-run emphasis to the post –Keynesian growth analysis of the Harrod Domar type. These developments considered both the short-term incomes creating effects and the long –run capacity –creating aspects of investment. In the final analysis, capital formation was assigned a decisive role in development process.

By the early 1950’s the Keynesian prescription of government intervention in the nation’s economic activities in order to promote growth received wide acceptance. Keynesian analysis with its later refinements was not applicable to an underdeveloped country because it had been cast in terms of the conditions existing in advanced countrie s. The policy measures, which flowed from the analysis, would yield different results when applied to a developing country. Suitable changes in economic priorities and in fiscal policy measures are required for countries at the stage of development.

Simon Kuznets (1952) observes that there is enormous variety in the different growth processes in the world.

For which reason, where there’s formulating or evaluating theoretical assumptions as to economic growth, any attempt to go beyond mere lists of factors would have to be made, bearing in mind the characteristics of countries and of the periods relating to the growth process it is intended to explain.

The determinants of growth methodology initiated by Moses Abramovitiz (1956) and Robert M Solow (1956) re lies heavily on the classical conception of an aggregate production function.. Solow’s (1956) growth theory, in its stripped –down model, asks the question: What are the determinants of sustainable growth of real income per person in an isolated economy producing a single product? This simple model assumes that the state of technology does not change over time, and that the labour does not grow, and capital stock does not depreciate.

Ricardo demonstrated that the ultimate outcome of the growth process rested up three basic propositions: (i) the Malthusian law of population, which held that population unless checked by disease, famine or war tends to expand at an exponential rate. (ii) The fundamental economic principle of diminishing return especially as applied to the scarce resource of agricultural land .

(iii) Theory of capital accumulation in which profit is a key variable.

The great importance of fiscal policy in many developing countries arises from the fact that the state, under democratic auspices, is called upon to play an active and important role in promoting economic growth. For various reasons, the governments of all developing countries virtually have been forced to play this role. In order to do this effectively, they have to interfere in the economic life of the country, control and regulate economic activities, and compel or induce people to behave in different ways at the cost of worsening its disincentive effects.

The only feature that is most common to most developing countries is the shortage of revenue, which makes it impossible for them to provide essential public services on the required scale. The inadequacy of public revenue has two important consequences. It forces undue economies precisely in those fields of public expenditure (like health and education) which are more easily sacrificed in the short run but are the most important from the point of view of long-run development. It also yields persistent budgetary deficits, which force the monetary authorities to follow highly restrictive credit policies (to protect the balance of payments and to limit the pace of inflation), which in turn has highly undesirable effects on the pace of economic growth.

Those who believe that insufficient growth and investment is mainly a consequence of a lack of resources are chiefly concerned with increasing the resources available for investment through additional taxation, even at the cost of worsening its disincentive effects. The only feature that is most common to most developing countries is the shortage of revenue which makes it impossible for them to provide essential public services on the required scale. The inadequacy of public revenue has two important consequences. It forces undue economies precisely in those fields of public expenditure (like health and education) which are more easily sacrificed in the short run but are the most important from the point of view of long-run development. It also yields persistent budgetary deficits, which force the monetary authorities to follow highly restrictive credit policies (to protect the balance of payments and to limit the pace of inflation), which in turn has highly undesirable effects on the pace of economic growth.

The resurgence of interest in growth theory may be linked to the twin contributions of Romer (1986) and Lucas (1988), who redirected the traditional focus on the accumulation of physical capital as a transitory source of growth to the accumulation of skills through education and training. Building on the foundations that Solow had established, these theorists incorporated technological change and imperfect competition to explain economic growth. One of the predictions of the neoclassical growth theory is that the growth rate of real income per capita of countries with identical preferences, technologies and population growth will converge over time due to higher rates of physical investment in the initially poorer countries, as capital moves in search of the higher rates of return.

A key assumption, following Lucas (1988), is that technology in each country is virtually identical; differences in income and productivity are thus entirely attributable to differences in relative factor endowments, human capital and physical capital stocks per worker.

Dhura Dhaheshwar and Micheal T., in their study on a large number of African countries, investigates empirically the determinants of economic growth for the period 1981-92. Their results indicate that an increase in private investments has a relatively large positive impact on per capita growth. They state that growth is stimulated by public policies that lower the budget deficit in relation to GDP. That convergence of per capita income occurs after controlling for capital development and public policies.

Hsing, Y. and Hsieh, W. examine the determinants of the growth rate of real output for China with an emphasis on institutional, social and political changes and developments. They found out that growth rate of real out put is positively correlated with employment growth or the change in employment to real output ratio, investment /output ratio, human capital, but negatively associated with the great leap forward, and the cultural revolution. The coefficients of deficit financing the openness of the economy , and dummy variables for economic and agricultural reforms are found to be insignificant.

Data and Variables

This work follows Easterly and Rebelo’s regression using data published by World Bank and from OECD National Accounts: Volume II (1983,1990,1996). A sample of 60 developing countries have been analyzed and the results compared with the arguments advanced by Easterly and Rebelo . We scrutinise the observations and drop the outliers. The countries dropped are Lebanon and Rwanda, otherwise if they were to be included, they would affect our results badly.

In preliminary work, we found that pushing the sample period back before 1970 sharply reduced the number of countries for which the data were available.

Summary statistics

Table 3. All the 60 countries

Variable Tax revenue Primary School Secondary school Total Revenue Government Debt Gov't consumption

Obs   Mean   Std. Dev.  

 
 
 
           
1028   5799   9.4  
           
754   5313   29.1  
           
742   3167   32.2  
           
1034   5506   11.3  
           
740   5636   46.1  
           
1835   3198   5.6  

As reflected in the table above the observation for schooling are few. This is mainly in the 60's and the 70's where data collection and storage was very expensive in developing countries.

Hypotheses

The following hypotheses are tested

1- Government Revenue /GDP rises with per capita income

2- Government consumption correla ted with growth.

3- Human capital is consistently correlated with growth

4- High government debt has a strong negative impact on growth.

5- Domestic taxes /GDP falls with increase per capita income

Model

gdp= ? + ? 1 tax +? 2

prm +? 3 sec +? 4 rev +? 5 dod

+ ? 6 con +?

where ; gdp – Growth rate per capita GDP(1960-1996) tax - Tax Revenue (% of GDP) prm - primary school enrollment(% gross) sec - secondary school enrollment(% gross) rev - Total Revenue(% of GDP) dod - Government debt (% of GDP) con - Government consumption (% of GDP)

School enrollment variables are included as proxies for the level of human capital

 

Empirical Analysis

Below we present simple correlation of fiscal variables with per capita growth rate Data range 1960 -1996 Correlation coefficient Tax revenue % of GDP -0.0875

Total Revenue % of GDP 0.0915 Government debt % of GDP -0.1036 Government consumption % of GDP -0.0915

We now look at the regression, starting with simple tax

regression as presented below.

Gdp= ? + ? tax +?

Below(table3), we have the coefficients and the t-statistics for tax revenue. As Easterly and Rebelo, our model predicts a detrimental effect on growth. Taxes affect the rate of growth by reducing the private returns to accumulation.

Table 3

GDP as dependent Variable Tax coefficient  


 
   All countries -0.497  
  (-2.74)  
     
African Countries 0.103  
  (2.16)  
     
Other Countries(excluding Africa) -0.091  
  (-5.89)  
 
 

Comparing African countries with other countries, we get a positive coefficient for tax

revenue in the case of African countries and a negative for others. This is explained by the fact that most African countries depend on taxes as a source of revenue to finance investment projects which lead to growth. Most investments in African countries are public investments thus the impact is greater than the distortionary effects.

When we expand our analysis by including the variable for primary and secondary education, we get a positive coefficient for primary, which is highly significant, but a negative coefficient for secondary. This explains that human capital is important for growth but it also indicates something to do with convergence. This will be explored later when we look at different groups of countries.

Table 2-7 shows results for the 57 countries by including one variable at time

Independent Variable Coefficient  


 
Tax revenue ( %GDP) -0.147  
  (-2.78)  
     
Primary school enrollment(% gross) 0.036  
  (2.90)  
     
Secondary school enrollment(% gross) -0.025  
  (-2.49)  
     
Total Revenue (% of GDP) 0.102  
  (2.28)  


 
     
     
     
     
     
     
     
Independent Variables Coefficient  


 

Tax Revenue(% of GDP) Primary school enronment Secondary School enronment Total Revenue Government Debt Government consumption

Table 5


------------------------------------------------------------------------------

      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | -.1481998   .0922807   -1.606   0.110   -.3300491   .0336494  
      prm | .0553792   .0167283   3.311   0.001   .0224141   .0883442  
      sec | -.0257697   .0124637   -2.068   0.040   -.0503307   -.0012087  
      rev | .1236253   .0730897   1.691   0.092   -.0204062   .2676567  
      dod | -.0047023   .0083226   -0.565   0.573   -.0211029   .0116983  
   _cons | .2451445   1.400707   0.175   0.861   -2.515105   3.005394  
                         
                         
Table 6                        

 
      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | -.1549699   .0924908   -1.676   0.095   -.3372422   .0273024  
      prm | .0525791   .0168629   3.118   0.002   .0193472   .085811  
      sec | -.0253909   .0124689   -2.036   0.043   -.0499634   -.0008183  
      rev | .1640287   .0783619   2.093   0.037   .0096004   .318457  
      dod | -.0018919   .0085836   -0.220   0.826   -.0188076   .0150238  
      con | -.0881509   .0627742   -1.404   0.162   -.2118605   .0355587  
   _cons | .8645315   1.467253   0.589   0.556   -2.026994   3.756057  


------------------------------------------------------------------------------

As indicated in tables above,we get a positive coefficient for government revenue as Easterly and Rebelo confirming the argument that the two are positively correlated. As shown in table 5 and 6 above, the effects of government debt is more complex. Government debt should reduce the rate of growth but we find the coefficient to be insignificant. There is a possibility of government debt to be correlated with government consumption. Regression results without debt variable gives a negatively significant coefficient for Government consumption.

Table 7.


------------------------------------------------------------------------------

      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | -.094908   .0740183   -1.282   0.201   -.2404411   .0506252  
      prm | .0360993   .0127814   2.824   0.005   .0109688   .0612298  
      sec | -.0270829   .0104549   -2.590   0.010   -.047639   -.0065269  
      rev | .0986297   .0628456   1.569   0.117   -.024936   .2221953  
      con | -.1138569   .0550627   -2.068   0.039   -.2221199   -.0055939  
   _cons | 3.238555   1.116368   2.901   0.004   1.043578   5.433532  


------------------------------------------------------------------------------

We also find out that GDP growth is negatively correlated with the government consumption levels as in Barro(1991), and Easterly and Rebelo.

When we expand our re gression by including other explanatory variables, one at a time, we find that the coefficients tend to be insignificant. This means that as we add on more variables, we lose some efficiency.

We continue to investigate the differences between African countries and others by adding more explanatory variables and the results are presented in tables 9 to 16. When we add the coefficient for primary and secondary for African countries, the coefficient of tax revenue is effected in fact it becomes insignificant hence a possibility that the three are correlated. With a panel set, containing a number of observations for each country, there may be country –specific effects, which are not captured by the explanatory variables, in which case the error term will be autocorrelated within country observations. Greene (1990) explains how it is possible to test for such effects and obtain unbiased estimates if they are present.

Table 9: African Countries

Gap | Coef. Std. Err.

t P>|t| [95% Con. Interval]

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

   Tax |.0464313 .0971075 0.478   0.633   -.1455091   .2383716  
   Prm |.0413782 .0282064 1.467   0.145   -.0143738   .0971303  
   Sec |-.0628632.0438091 -1.435   0.153   -.1494551   .0237287  
_Cons |1.110448 1.610153 0.690   0.492   -2.07214   4.293036  


------------------------------------------------------------------------------

Table 10: Others


------------------------------------------------------------------------------

Gap | Coef. Std. Err.   t   P>|t|   [95% Con. Interval]  
+--------------------------------------------------------------------  

 
      Tax |-.075571 .0273848   -2.760   0.006   -.1295054   -.0216366  
      prm | .0088549 .0176908   0.501   0.617   -.0259872   .043697  
      sec |-.0205624 .0108874   -1.889   0.060   -.0420052   .0008803  
   _cons | 6.078596 1.677689   3.623   0.000   2.77439   9.382803  


------------------------------------------------------------------------------

 

Table 11: African Countries


------------------------------------------------------------------------------

      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | -.1592803   .1778858   -0.895   0.372   -.5109482   .1923876  
      prm | .0352979   .0285398   1.237   0.218   -.0211234   .0917193  
      sec | -.0662998   .0440032   -1.507   0.134   -.1532911   .0206915  
      rev | .1784434   .1265216   1.410   0.161   -.0716811   .4285679  
   _cons | 1.447895   1.62803   0.889   0.375   -1.770609   4.6664  

 
                         
                         
Table 12: Others                      
                         
      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | -.1335267   .0423625   -3.152   0.002   -.2169661   -.0500873  
      prm | .0118427   .0177013   0.669   0.504   -.0230228   .0467082  
      sec | -.0259502   .0111989   -2.317   0.021   -.048008   -.0038923  
      rev | .0684725   .0384487   1.781   0.076   -.0072581   .1442031  
   _cons | 5.672878   1.692987   3.351   0.001   2.33828   9.007477  


------------------------------------------------------------------------------

Table 13: African Countries


------------------------------------------------------------------------------

      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | .1542716   .1799147   0.857   0.394   -.2044682   .5130114  
      prm | .0475866   .0363429   1.309   0.195   -.0248791   .1200524  
      sec | -.0910485   .0437026   -2.083   0.041   -.1781891   -.0039079  
      rev | .0852243   .1163317   0.733   0.466   -.1467346   .3171832  
      dod | -.0263112   .0216416   -1.216   0.228   -.0694633   .0168409  
   _cons | -2.406815   2.183507   -1.102   0.274   -6.760604   1.946973  


------------------------------------------------------------------------------

Table 14: others


------------------------------------------------------------------------------

      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | -.2480891   .1276637   -1.943   0.054   -.5003823   .0042041  
      prm | .0036076   .0216641   0.167   0.868   -.0392058   .0464209  
      sec | -.0362744   .0124495   -2.914   0.004   -.0608775   -.0116714  
      rev | .1685113   .1235886   1.363   0.175   -.0757287   .4127513  
      dod | .0048373   .0084579   0.572   0.568   -.0118774   .0215521  
   _cons | 7.356212   2.070698   3.553   0.001   3.264029   11.44839  


------------------------------------------------------------------------------

Table 15: African Countries                  
                         
      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | .1479619   .1810452   0.817   0.417   -.2131213   .5090451  
      prm | .0442782   .0369274   1.199   0.235   -.0293713   .1179276  
      sec | -.0900382   .0439348   -2.049   0.044   -.1776634   -.002413  
      rev | .0631813   .122562   0.516   0.608   -.1812609   .3076234  
      dod | -.0284667   .0220384   -1.292   0.201   -.072421   .0154875  
      con | .0926538   .155267   0.597   0.553   -.2170164   .4023239  
   _cons | -2.952889   2.376707   -1.242   0.218   -7.693082   1.787304  


------------------------------------------------------------------------------

Table 16: Others


------------------------------------------------------------------------------

      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | -.2851571   .1301354   -2.191   0.030   -.5423644   -.0279499  
      prm | -.0016587   .022057   -0.075   0.940   -.0452534   .041936  
      sec | -.0332063   .0126409   -2.627   0.010   -.0581904   -.0082221  
      rev | .2340355   .1312573   1.783   0.077   -.0253893   .4934603  
      dod | .0061913   .0085889   0.721   0.472   -.0107844   .0231669  
      con | -.0791448   .0591151   -1.339   0.183   -.1959834   .0376938  
   _cons | 7.974671   2.12245   3.757   0.000   3.779734   12.16961  


------------------------------------------------------------------------------

Table17-24 below, shows the results for the group wise regressions depending on the level of development. We have four groups arranged according to the level of development. Group 1 represents less developed countries.

We find a positive relationship between gdp and tax for less developed countries. As Easterly and Rebelo, we get a negative relationship for more developed countries.

Table 17: group 1


------------------------------------------------------------------------------

      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | .0772617   .0489096   1.580   0.115   -.0188894   .1734129  
   _cons | 2.578367   .9415528   2.738   0.006   .727371   4.429363  


------------------------------------------------------------------------------

Table 18: group 2


------------------------------------------------------------------------------

gdp | Coef.

Std. Err. t

P>|t| [95% Conf. Interval]

---------
+
--------------------------------------------------------------------
tax | -.4808518 .1135395 -4.235 0.000 -.7075408 -.2541628

_cons | 9.97274

1.63171 6.112

0.000 6.714926

13.23055


------------------------------------------------------------------------------

Table 19: group 3


------------------------------------------------------------------------------

      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | -.07821   .0208529   -3.751   0.000   -.1192185   -.0372016  
   _cons | 4.974114   .4824877   10.309   0.000   4.025274   5.922953  


------------------------------------------------------------------------------

Table 20: group 4

--
----------------------------------------------------------------------------

      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | -.1388482   .0203391   -6.827   0.000   -.1789898   -.0987067  
   _cons | 8.427535   .5661248   14.886   0.000   7.310224   9.544846  

 
                         
                         
Table 21: group 1                      
                         

 
      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | .0203214   .1033258   0.197   0.844   -.1837768   .2244196  
      prm | .0426921   .0300891   1.419   0.158   -.0167424   .1021267  
      sec | -.0844401   .0463384   -1.822   0.070   -.1759718   .0070916  
   _cons | 2.290504   1.705483   1.343   0.181   -1.078316   5.659323  


------------------------------------------------------------------------------

Table 22: group 2


------------------------------------------------------------------------------

      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | -.3860825   .1042955   -3.702   0.001   -.6008831   -.1712819  
      prm | .0643085   .0746992   0.861   0.397   -.0895374   .2181545  
      sec | .0150489   .0371781   0.405   0.689   -.0615207   .0916186  
   _cons | 2.065296   10.09487   0.205   0.840   -18.72548   22.85607  

 
                         
Table 23: group 3                      
      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | -.052597   .0572934   -0.918   0.360   -.1658222   .0606281  
      prm | -.0017037   .0223861   -0.076   0.939   -.0459438   .0425364  
      sec | -.0215855   .0181823   -1.187   0.237   -.0575179   .0143469  
   _cons | 6.158191   1.978682   3.112   0.002   2.247853   10.06853  


------------------------------------------------------------------------------

Table 24: group 4


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      gdp | Coef.   Std. Err.   t   P>|t|   [95% Conf. Interval]  
+--------------------------------------------------------------------  

 
      tax | -.0832185   .0285903   -2.911   0.005   -.1401988   -.0262382  
      prm | -.0417991   .0503737   -0.830   0.409   -.1421938   .0585955  
      sec | -.0672954   .0166108   -4.051   0.000   -.1004007   -.03419  
   _cons | 16.29064   5.330568   3.056   0.003   5.666832   26.91445  


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For group one, which represents less developed countries, the coefficient for tax revenue is insignificant. This is an indication that tax revenue in those countries does not affect GDP growth rates. From our results for the level of development above, we get a negative coefficient for secondary school enrollment for 3 groups. There is an indication of convergence hence in line with barro’s and Dhura’s findings about conditional convergence.

In this paper we also investigate the presence of endogeneity between GDP growth rate, tax revenue and government consumption, implying that the regressions that we reported are contaminated by simultaneous equation bias. We use the lagged variables as our instruments and the 2SLS test does not indicate presence of endogeneity

Summary and Conclusion

We have found out that government consumption and tax revenue are correlated with growth. That tax increases have detrimental effects on growth. This is because most countries depend on income tax as a source of tax revenue. The sharp increase in public expenditure relative to GDP and increase in tax burdens and fiscal deficits are seen as major cause of the difficulties many countries are facing in terms of sluggish economic growth.

The group wise results show that the impact of government consumption levels on GDP growth is indeed as predicted by Easterly and Robero.

Due to the shortage of voluntary savings, developing countries, especially African countries, are compelled to resort to high taxation as a device for mobilising resources needed for their development plans. We get positive coefficient for tax revenue for African countries hence a difference with Easterly and Rebelo’s results.

The empirical results in this study tend to suggest that the stages of economic development do indeed matter in identifying the variables that determine economic growth.

We also note the importance of human capital in the process of growth. The coefficient for secondary school is mainly negative.

The results thus predict conditional convergence.

The most important factors determining the process of economic growth appear to be tax revenue, government consumption and human capital.

 

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