Rural Structural Transformation in Developing Countries

Introduction

A key feature of economic development is structural transformation characterized by spatial and sectoral labor reallocation out of agriculture. Despite clear evidence of rural-urban migration flows in developing countries, recent contributions show persistently lower productivity in agriculture compared to other sectors and large disparity in agricultural productivity across space.

Research Question

This points to the key question of this proposal: “Why do so many workers remain in agriculture?” There is a pressing need for reliable answers to this question as rural areas host large shares of the population, facing high agricultural risk and poverty incidence.

Importance of Rural Development

Any effective poverty eradication policy, such as those envisioned by the UN’s Sustainable Development Goals, must therefore necessarily focus on rural development.

Methodology

RUSTDEC will obtain novel answers to this key question by combining innovative micro panel data from Sub-Saharan Africa and Southeast Asia with an array of geospatial data on rural areas, exogenous variation in agricultural productivity, and quantitative theoretical models.

Data Collection Techniques

The project employs remote-sensing and computer vision methods for generating community data as well as quasi-experimental and structural estimation techniques for rigorous causal estimation.

Objectives

The project aims to pursue three major objectives:

1. Provide first evidence on the role of dynamic adjustments in agricultural production for explaining the agricultural productivity gap and the magnitude of factor (mis-)allocation.
2. Dissect the microeconomic anatomy of spatial and sectoral labor reallocation and skill selectivity within and across rural communities.
3. Identify the historic and future impact of climate change on agricultural production, adaptation, and rural development and its implications for the productivity gap.

Contribution to Literature

These objectives address three well-defined gaps in the literature, each going beyond the specific state-of-the-art and with the potential of generating ground-breaking impact.