Economists and social scientists have long debated the relative importance of institutions and human capital as fundamental determinants of long-run development. After discussing some of the limitations of the existing literature, we use panel data covering the period 1955–2010 and a novel indicator of property rights protection from Varieties of Democracy (V-Dem) to reinvestigate these relationships. We find that both property rights institutions and human capital are positively related to economic growth, although human capital is relatively more robust when we account for country fixed effects. We also investigate whether the growth effects of property rights institutions are heterogeneous across different levels of development. In contrast to the cross-country evidence, our panel data results suggest that broad-based property rights protection clearly and strongly enhances growth only in advanced economies.
- Property rights
- Human capital
- Economic growth
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Contract enforcement, in addition, reduces transaction costs, clearing the way for the financial and commercial arrangements that are necessary to carry out investments. Yet, we focus here on the breadth of effective property rights enforcement.
Similarly, when the productive sector is small and, typically, connected through informal political or familial relations, Pareto-improving market exchanges could be sustained by personal relations of trust.
Their results are robust to using alternative indicators of institutional quality, such as Polity’s (Marshall et al. 2013) index of constraints on the chief executive from the Polity dataset, which has been a widely used proxy for the risk of expropriation.
A different objection, which Acemoglu et al. (2001: 1390) resist, is that instead of capturing the effect of the institutions brought by European settlers, the mortality instrument captures the effect of having “more Europeans”, who might have brought along a particularly developmental European culture.
Workers equipped with human capital are more productive, leading to a multiplicative relationship between labour (L) and human capital (H).
Some, though not all, growth accounting exercises have corroborated this pattern (see Helpman 2006).
As compared to the literacy and schooling rates of the average worker.
Alternatively, the correlation between human capital and institutions may result from joint determination by a third, more «fundamental» factor, such as culture (Bjornskov and Meon 2013).
These tests include the Kleibergen-Paap under-identification and weak identification tests.
The measures also aggregate across various kinds of property, such as land, financial investments and personal belongings.
Our panel results, however, are qualitatively consistent if we use OLS with heteroskedasticity-robust standard errors clustered at the country level. The results are available upon request.
In addition, we note that the rate of conditional convergence to the steady state, measured by the coefficient on lnY, increases when important determinants of the steady state (e.g. human capital, institutions) are included in the regression (as noted by Knack and Keefer 1995).
We also estimated pooled models without country fixed effects (μi). The results, available upon request, are qualitatively consistent with those of the cross-sectional regressions reported in Panel A (Table 18.1).
In addition, the results in panel B reproduce another important result from the empirical growth literature. When controlling for unobservable determinants of the steady state in fixed-effects panel models, the rate of conditional convergence to the steady state increases roughly by a factor of 10 (from 0.031 to 0.313), in line with the findings of Islam (1995).
We also instrument for lnYt − 1 to correct for dynamic panel (“Nickel”) bias. Standard tests (Arellano-Bond’s AR(2) test, and Hansen’s J-test) suggest that the instrument matrix satisfies the overidentifying restrictions.
The joint influence of omitted country characteristics (e.g. culture, history, geography) might itself be subject to the moderating influence of income levels. For instance, at low levels of income, the high estimated effect of institutions might possibly be biased upwards by the omission of country-specific characteristics that are beneficial for both institutional quality and growth at low income. The same omitted factors, however, may bias the institutional effect downwards at high income if they become growth-reducing, but still contribute to promoting institutional quality.
However, our findings are not driven by the case of China. Dropping China from the sample does not substantially alter the results reported in Table 18.3 (model 2, panel B). The results are available upon request.
=(0.84 − 0.42) × 0.273/5.
Or geography (Sachs 2003).
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Uberti, L.J., Knutsen, C.H. (2021). Institutions, Human Capital and Economic Growth. In: Douarin, E., Havrylyshyn, O. (eds) The Palgrave Handbook of Comparative Economics. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-50888-3_18
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