PS14- Spatial Econometrics
Tracks
ERSA2020 DAY 1
Tuesday, August 25, 2020 |
17:00 - 18:30 |
Room 2 |
Details
Chair: Dr. Julie Le Gallo, CESAER, France
Speaker
Prof. Massimo Giannini
Full Professor
Università di Roma Tor Vergata
Ageing in the labour market: a SpVar Approach
Author(s) - Presenters are indicated with (p)
Massimo Giannini (p), Cristiana Fiorelli, Barbara Martini
Abstract
Ageing is getting an important feature of European Countries and particularly for Italy. It opens to several questions related to pensions reforms, skills obsolescence, Neet and wage gap. Starting from a microfounded OLG models, we derive the optimal dynamic relationships for consumption and wealth in an economy populated by two living generations, workers and retired. These equations depend on worker age and this allows us to investigate on the effect of ageing on the dynamical paths. Log-linearization of the equations brings to a VAR model that can be estimated. Microdata come from the Bank of Italy Household Survey and aggregated by Italian regions (NUTS2). In order to take account for regional spillover, we augment the VAR with a neighborhood matrix, leading to a SpVar. Once estimated the SpVar, we invesigate the effect of ageing on the endogenous variables by means of the impulse response functions.
Mr Takahiro Tsukamoto
Ph.D. Student
Nagoya University
Yardstick Competition and Spatial Interdependence of Cost Efficiency in Local Governments: Development of an Interpretable Spatial Inefficiency Stochastic Frontier Model
Author(s) - Presenters are indicated with (p)
Takahiro Tsukamoto (p), Izuru Maeda
Abstract
A wide variety of spatial stochastic frontier models, which merge stochastic frontier models and spatial econometric models, have been proposed. However, these models have not been clarified in a systematic way. Thus, we introduce (non-spatial) stochastic frontier models and basic models of spatial econometrics, systematically categorize the spatial stochastic frontier models, and then clarify the characteristics and problems of each.
Then, we develop a new spatial inefficiency stochastic frontier model. Our spatial inefficiency stochastic frontier model meets the following conditions: (a) It can detect not only positive, but also negative spatial autocorrelation of inefficiency; (b)The inefficiency follows a truncated normal distribution; and (c) It can distinguish whether the detected spatial autocorrelation is caused by an influence from one’s own inefficiency on the surrounding inefficiency (true spatial spillovers) or by a lack of spatially dependent determinants of inefficiency (apparent spatial spillovers).
Furthermore, we theoretically show that yardstick competition between local governments leads to the spatial interdependence of inefficiency. And then, we use our proposed model to verify whether there is a spatial interdependence of cost inefficiency in Japanese local governments. Our results support that yardstick competition between Japanese local governments is present. It implies that the disclosure of information on local government activities will lead to better efficiency.
Then, we develop a new spatial inefficiency stochastic frontier model. Our spatial inefficiency stochastic frontier model meets the following conditions: (a) It can detect not only positive, but also negative spatial autocorrelation of inefficiency; (b)The inefficiency follows a truncated normal distribution; and (c) It can distinguish whether the detected spatial autocorrelation is caused by an influence from one’s own inefficiency on the surrounding inefficiency (true spatial spillovers) or by a lack of spatially dependent determinants of inefficiency (apparent spatial spillovers).
Furthermore, we theoretically show that yardstick competition between local governments leads to the spatial interdependence of inefficiency. And then, we use our proposed model to verify whether there is a spatial interdependence of cost inefficiency in Japanese local governments. Our results support that yardstick competition between Japanese local governments is present. It implies that the disclosure of information on local government activities will lead to better efficiency.
Prof. Daniel Felsenstein
Full Professor
Hebrew University of Jerusalem
A Solution for Absent Spatial Data: the Common Correlated Effects Estimator
Author(s) - Presenters are indicated with (p)
Daniel Felsenstein (p), Michael Beenstock
Abstract
Informed regional policy needs good regional data. As regional data series for key economic variables are generally absent whereas national-level time series data for the same variables are ubiquitous, we suggest an approach that leverages this advantage. We hypothesize the existence of a pervasive 'common factor' represented by the national time series that affects regions differentially. We provided an empirical illustration in which national FDI is used in place of panel data for FDI, which are absent. The proposed methodology is tested empirically with respect to the determinants of regional demand for housing. We use a quasi-experimental approach to compare the results of a 'common correlated effects' (CCE) estimator with a benchmark case when absent regional data is omitted. Using three common factors relating to national population, income and housing stock, we find mixed support for the common correlated effects hypothesis. We conclude by discussing how our experimental design may serve as a methodological prototype for further tests of CCE as a solution to the absent spatial data problem.
Prof. Julie Le Gallo
Full Professor
CESAER
Tax competition with intermunicipal cooperation
Author(s) - Presenters are indicated with (p)
David Agrawal, Marie-Laure Breuillé , Julie Le Gallo (p)
Abstract
We study local tax competition when municipalities can voluntarily cooperate with neighboring jurisdictions. In France, cooperation occurs by forming an “establishment for inter-municipal cooperation” (EIMC). Joining an EIMC amounts to agreeing to finance joint projects, while still allowing the municipality to maintain taxing power. We study how tax competition and interjurisdictional policy interdependence differ between competing municipalities within the same EIMC and competing municipalities outside of the cooperative unit. We apply the estimation strategy of Kelejian and Piras (2014) to resolve the endogeneity of the decision to cooperate with other municipalities. To do this, we instrument for current day cooperation with the historical participation decisions in unrelated cooperative agreements forty years earlier. When studying the effect of cooperation on taxes, we find that tax competition among peer members of the same EIMC is less intense than tax competition with municipalities outside of the cooperative unit. The results are consistent with inter-municipal cooperative units reducing parasitic tax competition with respect to municipal tax rates.
Abstract
Abstract