Governance and Growth: An Application to Bangladesh

In the 19th century, many thought that specialization and division of labor was the engine of growth. In the 20th century, the driving force for economic growth was considered to be investment in physical capital and infrastructures. Later, human capital, technological progress (whether created by the country or copied from advanced economies) and governance are considered central determinants of economic growth (Barro 1991; 1997). The higher growth rate in least developed countries including Bangladesh would lift people out of poverty as their incomes rise and make improvements in other development dimensions such as reductions in infant mortality, longer life expectancy, increased access to water and sanitation, expanded education, reduced female discrimination and declines in child labor. Poor governance has been an important constraint on growth in Bangladesh.

Traditionally, the causal relationship between governance and growth is estimated by regressions with the aid of instrumental variables. The instrumental variables are used to deal with biases caused by measurement errors, omitted variables and endogeneity. The general effect of quality of governance on the level of income is measured by one standard deviation (see Mauro 1995). There are quite a few attempts to link perceptions of governance with development outcomes to explore casual relationships across countries. Data availability in governance research for longer periods remains a great problem. As a result, broad patterns of interrelationships that affect governmental outcomes are often incorporated into explanations and research findings. Nevertheless, the empirical research over the last decade has given us some basis to gauge the effects of governance on development.

The available evidence in a number of studies across countries suggests that better maintenance of the rule of law market distortions and political stability affect economic growth (Barro 1991: 1997). IMF empirical study (2003) using geographic variables as instruments, found that governance has a statistically significant impact on GDP per capita across ninety-three countries and the governance explain nearly 75 per cent of the cross country variations in income per head. Hurther and Shah study (2005, chapter 2) found that there is a high correlation between governance quality and per capita income. The positive correlation between the 10-year economic growth rate and governance quality supports the argument that it is an important determinant in economic development. Since the highest income countries have generally not had the highest growth rates over the last decade, the positive correlation between higher growth and better governance suggests that good governance improves economic performance rather than vice versa.

Kaufmann et al. (2002) found direct casual effect from better governance to higher per capita income across countries pertaining to 175 countries for the period 2000/01. Negative causal effect is found as well from per capita income to governance implying that improvements in governance are unlikely to occur merely as a consequence of development. The simple correlation coefficient between per capita income and quality of governance are strongly positive since the strong positive effects of governance dominate the correlation result. Using the technique of non-sample information (out-ofsample technique) through the Unobserved Component Model, the authors do not find positive feed back from higher income to better governance outcomes (see Kaufmann and Kraay. 2002). Two hundred years ago, per capita incomes were not very different across countries. The recent research attributes a substantial part of vast differences in long run growth to huge historical differences in governance quality.

Mauro (1995) constructed a subjective index of bureaucratic efficiency (proxy for corruption) as an average of three components: Efficiency of the Judiciary System, Red tape, and Corruption, to provide empirical evidence of the effects of corruption on economic growth. The indices are integers between 0 and 10 and a high value of the index meaning a better outcome. The negative association between corruption and investment, as well as growth, has been found significant in both a statistical and an economic sense in his cross-country study. A one-standard-deviation improvement in the bureaucratic efficiency (corruption) index is associated with a 1.3 (0.8) percentage point (absolute) increase in the annual growth rate of GDP per capita. For Bangladesh, a one-standard-deviation increase in the bureaucratic efficiency index corresponds to a rise of its investment rate by almost five percentage points, and its yearly GDP growth rate would rise by over half a percentage point.

Rahman et al’s paper (2000) extends the pioneering work of Mauro (1995) covering data in the 1990’s (1991-97). International Country Risk Guide (ICRG) corruption index is chosen as proxy for corruption in this paper. As noted earlier, corruption is most prevalent where there are weak institutions, political governance failures and low level of ICT. Using a cross-country econometric model, this study has shown that corruption significantly reduces the growth of per capita GDP in Bangladesh, and if corruption in Bangladesh could be reduced to levels existing in economies like Poland, during the 1990-97 period, Bangladesh could have increased its annual average per capita growth rate by more than 2 percent. Over a short period of time (8 years), Bangladesh per capita GNP would have increased by 18% increase compared to the actual 1997 per capita GNP of $350. Bangladesh 2020 report (reprinted in Rahman, 2000) shows that incidence of extreme poverty would be reduced from the current 36 percent to about 11 percent by the year 2020 if the economic growth increases further by 2-3 per cent per annum.

A modest attempt is made here to link gross national product per capita with the governance dimensions employing 2SLS and OLS methods. Relationship between governance dimensions and average per capita GNP is expected to be positive, as in other cross-country studies stated earlier. The recent available data are used to estimate the equations. GNP per capita is the average of two years 2003 and 2002. Each of the governance measures is highly correlated with per capita GNP across country. Both ordinary least squares and 2SLS methods are applied to estimate the casual links. Table 18 reports regression results for the relationship between GNP per capita and each of governance dimensions. The focal variables, political governance, institutional dimension, and ICT are found to be both economically and statistically significant. The direction of causality between GNP per capita and governance dimensions has remained unchanged with the application of both OLS and 2SLS methods where five year lagged values of the independent variables, human capital (secondary school enrollment is used as a proxy) and ICT are incorporated into the equation. But the coefficients of focal variables change to a certain extent when 2SLS is applied. Usually, there is no correlation between the disturbance and the lagged values (Iimi 2005). Moreover there is a strong correlation between per capita income and governance indicators. Literally speaking, if political governance improves to the level of Thailand, GNP per capita would increase by more than 3.5 USD at PPP per annum holding other things constant. Researchers tend to estimate the growth equation with or without investment as an explanatory variable. In our study, using gross capital formation in the equation, the level of coefficients and direction of political governance remains unchanged as being positive and significant.

Similarly, the impact of public institutions on GNP per capita has been assessed with the application of both OLS and 2SLS methods. The public institutions have been found to be significant and positive. If the quality of public institutions could be improved to the level of Malaysia, Bangladesh GNP per capita would have increased by USD 11 at PPP in one year. The coefficient of public institutions is found much higher than that of political governance (Regressions 1 to 4). The coefficient of public institutions is estimated to be .085 while that for political governance is .061. The result indicates that better public institutions will have much greater impact on the Bangladesh economy compared to other governance dimensions, although the three dimensions under study are inter-related. As mentioned in section 4.2 the performance of Bangladesh on public institutions shows a dismal picture. Judicial independence is the number one element of public institutions and Bangladesh performance is lower compared to other countries (Figure 10 [ PDF 173.7KB | 25 pages ]).

It may be noted that the ICT dimension is highly significant in all the equations with political governance and public institutions variables. The separate estimation on the causal relationship of ICT with GNP per capita provides the same significant results (regressions 5 & 6). What appears is that political governance, public institutions and ICT have positive influence on GNP per capita. The three governance dimensions are assessed together by OLS method to see the extent of their effects on per capita income and the results are reported in regression 7 of Table 18 [ PDF 173.7KB | 25 pages ]. Due to application of OLS method, the estimated equation may have problems of multicolinearity and endogeneity bias. The results show that the impact of ICT seems to be greater on per capita income, followed by political governance. The un-weighted decomposition analysis among political governance, public institutions and ICT reveals public institutions as most significant (39%) followed by political dimension (35%) and ICT (26%). The Principal component Analysis identified them as principal component variables in order of similar significance. It can be safely said that the improved performance of public institutions will bring greater significant impact on overall improvement of governance dimension as well as higher growth in the economy, although they are interrelated.

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