Jonas GATHEN will defend his thesis on Tuesday 2 July at 15:00 (Auditorium 5, Building TSE)
« Essays in Macro Development»
Supervisors: Fabrice Collard and Stéphane Straub
To attend the conference, please contact the secretariat Christelle Fotso Tatchum
Memberships are:
- Fabrice COLLARD : Senior Researcher, CNRS/TSE-R Directeur de thèse
- Matteo BOBBA : Professor in Economics, TSE-R / University of Toulouse Capitole Examinateur
- Francisco BUERA : Professor in Economics, Washington University in St Louis Rapporteur
- Josep PIJOAN-MAS : Professor in Economics, CEMFI Rapporteur
Abstract :
What drives economic growth and development and how do poorer countries become richer? This fundamental question on the Macroeconomics of Development is the underlying motivation for this thesis. The three chapters focus on different aspects of the development process.
In the first chapter, co-authored with Oscar Fentanes, we ask how to quantify the effect of policies in economies where firms face adjustment frictions and the economic environment changes constantly. In such settings, at any given point in time, the economy responds to new changes in policy while still adjusting to previous changes. We show how to empirically disentangle the two using a structural model of plant dynamics and standard plant-level panel data. We apply our approach to the Indonesian Growth Miracle from 1975 to 2015, estimating the model on 40-years of micro data along the observed growth path without assuming that the economy is ever at a steady state. We find that growth from catching-up to previous changes in the economy starting from initial conditions in 1975 accounts for 42% of Indonesia’s subsequent industrialization. However, rapid changes in the economy induce new growth, such that the economy in 2015 is as far away from its steady state as in 1975.
In the second chapter, I quantify the aggregate costs of political connections using a general equilibrium model in which politically connected firms benefit from output subsidies and endogenously spend resources on rent-seeking activities. The model is structurally estimated using rich firm-level data for the Indonesian manufacturing sector and a firm-level measure of political connectedness based on a natural experiment from the authoritarian rule of Suharto at the end of the 1990s. A major innovation is to non-parametrically identify the output subsidy from differences in distributions of revenue-based total factor productivity (TFP) across connected and non-connected firms. In general equilibrium, both the distribution and the level of
subsidies to connected firms matter. I find that subsidies to connected firms are too high and dispersed, costing the economy between 1.0-4.7% of aggregate output. At most, 45% of these output costs are due to the misallocation of factors of production towards connected firms. The large remainder is explained by the costs of subsidizing connected firms instead of putting saved subsidies to more productive use.
The third chapter in my thesis provides a new approach to estimate government worker skills, a key input to study how the composition and selection of government workers drives state capacity and development. The approach is applicable in settings where government output is unobserved and government wages are uninformative about skill differences. The three-step approach first estimates skills from wages in comparable jobs in the private sector, then relates these skills to skill-related observables using Machine Learning tools and finally predicts government worker skills out-of-sample. I apply the new estimation approach to rich Indonesian household-level panel data from 1988 to 2014, showing two main applications. First, I quantify that government workers are highly selected, that their skills have increased, but that their skill premium has declined over time. Second, I analyze government wage setting: the Indonesian government pays a wage premium of at least 30% conditional on skills, about 1/3 of which is driven by the large gender wage gap in Indonesia's private sector.
