Does Econometric Methodology Matter? An Analysis of Public Policy Using Spatial Econometric Techniques

Do parties learn from or emulate parties in other political systems? This research develops the argument that parties are more likely to employ the heuristic of learning from and emulatingforeign successful (incumbent) parties. Spatial-econometric analyses of parties’ election policies from several established democracies robustly confirm that political parties respond to left-right policy positions of foreign political parties that have recently governed. By showing that parties respond to theseforeign incumbent parties, this work has significant implications for our understanding of party competition. Furthermore, we contribute to the literature on public policy diffusion, as we suggest that political parties are important vehiclesthroughwhich public policies diffuse.

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Selected Challenges from Spatial Statistics for Spatial Econometricians

Comparative Economic Research ◽

10.2478/v10103-012-0027-5 ◽

2013 ◽

Vol 15 (4) ◽

pp. 71-85 ◽

Cited By ~ 2

Author(s):

Daniel A. Griffith

Keyword(s):

Spatial Autocorrelation ◽

Spatial Statistics ◽

Random Effects ◽

Spatial Econometrics ◽

Random Variable ◽

Spatial Econometric ◽

Massive Datasets ◽

Topological Features ◽

Eigenvector Spatial Filtering ◽

Econometric Methodology

Griffith and Paelinck (2011) present selected non-standard spatial statistics and spatial econometrics topics that address issues associated with spatial econometric methodology. This paper addresses the following challenges posed by spatial autocorrelation alluded to and/or derived from the spatial statistics topics of this book: the Gaussian random variable Jacobian term for massive datasets; topological features of georeferenced data; eigenvector spatial filtering-based georeferenced data generating mechanisms; and, interpreting random effects.

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Climate Sensitivity and the Value of Agricultural Production in the Brazilian Northeast: An Approach Using Spatial Panel Data

International Journal of Business Administration ◽

10.5430/ijba.v12n5p65 ◽

2021 ◽

Vol 12 (5) ◽

pp. 65

Author(s):

Helson Gomes De Souza ◽

Pablo Urano de Carvalho Castelar ◽

Edward Martins Costa ◽

Francisco Jose Silva Tabosa

Keyword(s):

Agricultural Production ◽

Spatial Econometric ◽

Average Temperature ◽

Production Value ◽

Spatial Panel Data ◽

Econometric Methodology ◽

Temperature Levels ◽

Space Data ◽

Brazilian Northeast ◽

Precipitation And Temperature

This work analyzes the sensitivity of agricultural production in relation to changes in precipitation and temperature levels in the Northeast region of Brazil. For that purpose, data from 2006 to 2016 were used for 952 municipalities in the area. The econometric methodology derived from Kunwar and Bohara (2017) and is applied to the production value of municipalities in the Brazilian Northeast, where it is assumed that the production value is also impacted by the interactions between precipitation and temperature. Thus, time and space data are used, applied to a spatial econometric methodology. The results suggest that the agricultural production of the municipalities of the Brazilian Northeast is spatially autocorrelated. There is indication that there are municipalities with high (or low) levels of production, which have neighbors with these same characteristics. It was also verified that, from 2006 to 2011, the agricultural production was more sensitive to changes in temperature levels than to changes in average precipitation. However, after the years 2012, 2013, 2015 and 2016, agricultural production has become more sensitive to changes in the precipitation levels. It was also noted that in the analyzed period there was an increase in the average sensitivity of the agricultural production in relation to the precipitation levels, while the average temperature sensitivity showed a decrease.

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