1,721,121 research outputs found
Unobservable factors and panel data sets: an investigation in the labour market
No full textThis paper investigates the effects of unobservable factors that, as is well-known, contaminate two of the variables most used in labour market research, namely the stock of unemployment and the stock of vacancies. Using a matching function framework, we compare different panel data estimators using a number of appropriate Hausman tests robust to deviations from the classical errors assumptions. The relevance of the choice of the model specification is underlined. It is shown to what extent conclusions lacking a rigorous statistical analysis may be misleading
Geography and economic performance: exploratory spatial data analysis for Great Britain
No full textThis paper uses the techniques of exploratory spatial data analysis to examine patterns of spatial association for different indicators of economic performance and in so doing identifies and describes the spatial structure of economic performance in Great Britain
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Influencing connected legislators
Full text linkThis paper studies how interest groups allocate campaign contributions when congressmen are connected by social ties. We establish conditions for the existence of a unique Nash equilibrium in pure strategies for the contribution game and characterize the associated allocation of the interest groups’ moneys. While the allocations are generally complex functions of the environment (the voting function, the legislators’ preferences, and the social network topology), they are simple, monotonically increasing functions of the respective legislators’ Katz-Bonacich centralities. Using data on the 109th–113th Congresses and on congressmen’s alumni connections, we estimate themodel and find evidence supporting its predictions
Treatment Effects With Heterogeneous Externalities
Full text linkThis article proposes a new method for estimating heterogeneous externalities in policy analysis when social interactions take the linear-in-means form. We establish that the parameters of interest can be identified and consistently estimated using specific functions of the share of the eligible population. We also study the finite sample performance of the proposed estimators using Monte Carlo simulations. The method is illustrated using data on the PROGRESA program. We find that more than 50% of the effects of the program on schooling attendance are due to externalities, which are heterogeneous within and between poor and nonpoor households
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