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Ms. Helene Poirson Ward
This study seeks to explain economic growth differences in an aggregate production function framework, where labor reallocation from agriculture to modern sectors influences labor efficiency growth. The econometric analysis uses a panel of 65 countries over 1960-90. The results highlight: (a) the differences in labor reallocation impact on growth, controlled for using the intersectoral wedge in labor productivities; (b) the significance of labor reallocation effects, even after controlling for capital accumulation, initial conditions, and country effects; (c) the role of slow labor reallocation in explaining the dummy variable for Sub-Saharan Africa; (d) the role of initial education levels in explaining differences in labor reallocation rates.
Helene Poirson

, relative labor productivity, and employment share variables. For each variable, there are between one and six observations per country. When the education (resp. reallocation) variables are included, the sample is restricted to 75 (resp. 65) countries, and a total of 422 (resp. 309) observations. The data and the list of countries (Table Al) are presented in more detail in the Appendix . A. Estimation results The results are presented in Table 1 . Regressions were run using OLS (with fixed effects) and the White estimation method (variance-covariance matrix

Ms. Helene Poirson Ward

finding relevant instruments for the reallocation variables precludes it here. 5 Before 1965, data are missing for an important number of countries. 6 The (negative) catch-up effect is relatively stronger though for slow-growth countries.