Structural Change and Cross-Country Growth Empirics

Abstract

One of the most striking features of economic growth is the process of structural change whereby the share of agriculture in GDP decreases as countries develop. The crosscountry growth literature typically estimates an aggregate homogeneous production function or convergence regression model that abstracts from the process of structural change. In this paper, we investigate the extent to which assumptions about aggregation and homogeneity matter for inferences regarding the nature of technology differences across countries. Using a unique World Bank dataset, we estimate production functions for agriculture and manufacturing in a panel of 40 developing and developed countries for the period from 1963 to 1992. We empirically model dimensions of heterogeneity across countries, allowing for different choices of technology within both sectors. We argue that heterogeneity is important within sectors across countries implying that an analysis of aggregate data will not produce useful measures of the nature of the technology or productivity. We show that many of the puzzling elements in aggregate crosscountry empirics can be explained by inappropriate aggregation across heterogeneous sectors. JEL codes: O47, O11, C23 The early literature on developing countries distinguished between the processes of economic development and economic growth. Economic development was considered a process of structural transformation by which, in Arthur

The Magnitude of the Task Ahead: Macro Implications of Heterogeneous Technology

“…A more formal treatment of technology heterogeneity is provided in Mundlak et al . () and linked to the empirical framework that we adopt here in Eberhardt and Teal ().…”

“…Yet in contrast to the literature on cross‐country growth regressions using aggregate economy (Durlauf et al ., ) or agriculture data (Mundlak et al ., ; Eberhardt and Teal, 2013a,b, and references therein), there is comparatively little empirical work dedicated to the analysis of the manufacturing sector in a large cross‐section of countries—with the exception of studies on the dual economy model (e.g. Martin and Mitra, ; Eberhardt and Teal, 2013a,b), and recent work by Dani Rodrik (Rodrik, ; McMillan et al ., ), cross‐country empirical analysis at the sectoral level is typically limited to the investigation of OECD economies (Bernard and Jones, 1996a,b; Eberhardt et al ., ). If manufacturing matters for development, it is self‐evidently important to learn about the production process and its drivers in this industrial sector.…”

Does Openness Matter for Financial Development in Africa?

“…Although the economic interpretation of the common factor ( t f ) is not straightforward in a production function context, Eberhardt and Teal (2013) argue that it could be viewed as a measure of total factor productivity (TFP). In the context of this paper, the common factor could capture, for example, the impact of technological change (such as the introduction of ATMs or mobile phone technology) on financial development.…”

No Mangoes in the Tundra: Spatial Heterogeneity in Agricultural Productivity Analysis*

“…Note that country‐specific parameter coefficients should not be viewed in isolation (Pedroni, 2007, p. 440), frequently yielding economically implausible magnitudes (Boyd and Smith, 2002), as is illustrated by the extreme values of the distribution in the present case, –2.30 and 3.05. In Eberhardt and Teal (forthcoming), we provide a formal explanation for the occurrence of these implausible country estimates alongside the much more sensible average values.…”