Calendrier du 26 février 2024
Econometrics Seminar
Du 26/02/2024 de 16:15 à 17:30
PSE, room R1-15
DHAENE Geert (KU Leuven)
Iterated corrections for incidental parameter bias
écrit avec Co-authors: Koen Jochmans and Martin Weidner
In many panel data models, fixed effects typically lead to an incidental parameter problem: maximum likelihood estimation of the model’s common parameters (e.g., common slope or variance parameters) is often biased/inconsistent as the number of cross-sectional units grows large while the number of time periods is fixed (Neyman and Scott 1948). I will discuss two methods to correct for incidental parameter bias. Their power lies in the fact that they can be iterated. (1) The first method, called approximate functional differencing, has a Bayesian flavor. It uses the posterior predictive density to construct a q-th order bias corrected score function, starting from an initially chosen (biased) score function. In the limit as q goes to infinity, the method is equivalent to Bonhomme’s (2012) method of functional differencing in point-identified models. When point identification fails, the limit remains well defined and yields estimates with very small bias. (2) The second method is entirely frequentist. Starting from the (biased) profile score function, it constructs a bias corrected score function by calculating the bias as a function of the incidental parameters and using maximum likelihood estimates thereof as plug-in estimates, and it iterates these steps. In several models, it is found that the first-order bias corrected profile score function is already exactly unbiased, hence resolving the incidental parameter problem. In other models, the infinitely iterated bias correction leads to estimates with very small bias. (This presentation is based on joint work with Martin Weidner and older work with Koen Jochmans.)
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Paris Migration Economics Seminar
Du 26/02/2024 de 12:30 à 13:30
R1-14
AGER Philipp (Mannheim University)
Gender-biased technological change: Milking machines and the exodus of women from farming
This paper studies the link between gender-biased technological change in the agricultural sector and structural transformation in Norway. After WWII, Norwegian farms began widely adopting milking machines to replace the hand milking of cows, a task typically performed by women. Combining population-wide panel data from the Norwegian registry with municipality-level data from the Census of Agriculture, we show that the adoption of milking machines triggered a process of structural transformation by displacing young rural women from their traditional jobs on farms in dairy-intensive municipalities. The displaced women moved to urban areas where they acquired a higher level of education and found better-paid employment. These findings are consistent with the predictions of a Roy model of comparative advantage, extended to account for task automation and the gender division of labor in the agricultural sector. We also quantify significant inter-generational effects of this gender-biased technology adoption. Our results imply that the mechanization of farming has broken deeply rooted gender norms, transformed women’s work, and improved their long-term educational and earning opportunities, relative to men.
Régulation et Environnement
Du 26/02/2024 de 12:00 à 13:30
R1-09
DURRMEYER Isis (TSE)
*The Welfare Consequences of Urban Traffic regulations
écrit avec Nicolas Martinez (TSE)
We develop a structural model to represent individual transportation decisions, the equilibrium road traffic levels, and speeds inside a city. The model is micro-founded and incorporates a high level of heterogeneity: individuals differ in access to transportation modes, values of travel time, and schedule constraints; road congestion technologies vary within the city. We apply our model to the Paris metropolitan area and estimate the model parameters from publicly available data. We predict the road traffic equilibria under driving restrictions and road tolls and measure the policy consequences on the different welfare components: individual surplus, tax revenues, and cost of emissions.