Results 1  10
of
57
Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure
, 2004
"... This paper presents a new approach to estimation and inference in panel data models with a multifactor error structure where the unobserved common factors are (possibly) correlated with exogenously given individualspecific regressors, and the factor loadings differ over the cross section units. The ..."
Abstract

Cited by 150 (31 self)
 Add to MetaCart
This paper presents a new approach to estimation and inference in panel data models with a multifactor error structure where the unobserved common factors are (possibly) correlated with exogenously given individualspecific regressors, and the factor loadings differ over the cross section units. The basic idea behind the proposed estimation procedure is to filter the individualspecific regressors by means of (weighted) crosssection aggregates such that asymptotically as the crosssection dimension ( N) tends to infinity the differential effects of unobserved common factors are eliminated. The estimation procedure has the advantage that it can be computed by OLS applied to an auxiliary regression where the observed regressors are augmented by (weighted) cross sectional averages of the dependent variable and the individual specific regressors. Two different but related problems are addressed: one that concerns the coefficients of the individualspecific regressors, and the other that focusses on the mean of the individual coefficients assumed random. In both cases appropriate estimators, referred to as common correlated effects (CCE) estimators, are proposed and their asymptotic distribution as N →∞, with T (the timeseries dimension) fixed or as N and T →∞(jointly) are derived under different regularity conditions. One important feature of the proposed CCE mean group (CCEMG) estimator is its invariance to the (unknown but fixed) number of unobserved common factors as N and T →∞(jointly). The small sample properties of the various pooled estimators are investigated by Monte Carlo experiments that confirm the theoretical derivations and show that the pooled estimators have generally satisfactory small sample properties even for relatively small values of N and T.
Strategic interaction among governments: An overview of empirical studies
 International Regional Sience Review
, 2003
"... This article provides an overview of empirical models of strategic interaction among governments. To clarify the theoretical roots of such studies, the discussion shows how the empirical frameworks fit into two broad categories: spillover models and resourceflow models. Both types of models generat ..."
Abstract

Cited by 69 (0 self)
 Add to MetaCart
This article provides an overview of empirical models of strategic interaction among governments. To clarify the theoretical roots of such studies, the discussion shows how the empirical frameworks fit into two broad categories: spillover models and resourceflow models. Both types of models generate jurisdictional reaction functions, and the empirical task is to estimate such functions. When the estimated reactionfunction slope is nonzero, the presence of strategic interaction is confirmed. The second part of the article reviews three econometric issues relevant to this estimation problem.
Under the hood: issues in the specification and interpretation of spatial regression models
 Agricultural Economics
, 2002
"... This paper reviews a number of conceptual issues pertaining to the implementation of an explicit “spatial ” perspective in applied econometrics. It provides an overview of the motivation for including spatial effects in regression models, both from a theorydriven as well as from a datadriven persp ..."
Abstract

Cited by 44 (1 self)
 Add to MetaCart
This paper reviews a number of conceptual issues pertaining to the implementation of an explicit “spatial ” perspective in applied econometrics. It provides an overview of the motivation for including spatial effects in regression models, both from a theorydriven as well as from a datadriven perspective. Considerable attention is paid to the inferential framework necessary to carry out estimation and testing and the different assumptions, constraints and implications embedded in the various specifications available in the literature. The review combines insights from the traditional spatial econometrics literature as well as from geostatistics, biostatistics and medical image analysis.
The doughboys networks: Social interactions and labor market outcomes of World War I veterans. mimeo
, 2011
"... This paper examines the e¤ect of social networks on the postwar employment of American WWI veterans. The groups I examine were all formed due to a quasirandom event, the WWI draft. Service in the same military unit de…nes an individual’s reference group. I construct a new dataset where I observe a ..."
Abstract

Cited by 11 (0 self)
 Add to MetaCart
This paper examines the e¤ect of social networks on the postwar employment of American WWI veterans. The groups I examine were all formed due to a quasirandom event, the WWI draft. Service in the same military unit de…nes an individual’s reference group. I construct a new dataset where I observe all members of each group and link the veterans to the Census of 1930. In addition, I obtain their prewar outcomes for use as a control. I …nd that a group’s unemployment rate has a negative e¤ect on a veteran’s own likelihood of being employed. For example, in the 1930 census, the marginal e¤ect of a 10percentagepoint increase in his peers’unemployment rate, all else equal, decreases a veteran’s likelihood of employment by three to four percentage points. I then introduce a new framework which allows for further decomposing the e¤ect into its two components, the endogenous (“the e¤ect of others’outcomes”), and the contextual (“the e¤ect of others’characteristics”). I show that the two e¤ects are separately identi…ed, provided that some people belong to more than one group. The framework is applicable in other settings, since in many cases individuals are potentially a¤ected by multiple circles of in‡uence (e.g., neighborhood and family, or high school and college). I demonstrate an application of this framework using for each of the veterans in the sample two types of reference groups, those who had served with him during WWI, and a group of his closest (in terms of distance) neighbors in the 1930 census. I …nd the endogenous e¤ect to be much stronger than the contextual e¤ect.
Specification and Estimation of Social Interaction Models with Network Structure, Contextual Factors, Correlation and Fixed Effects
, 2008
"... This paper considers the specification and estimation of social interaction models with network structures and the presence of endogenous and contextural e¤ects. With macro group settings, group fixed effects are also incorporated. Networks provide information on the identification of endogenous, ex ..."
Abstract

Cited by 8 (3 self)
 Add to MetaCart
This paper considers the specification and estimation of social interaction models with network structures and the presence of endogenous and contextural e¤ects. With macro group settings, group fixed effects are also incorporated. Networks provide information on the identification of endogenous, exogenous and unobserved interactions among specific peers. We consider the identification and estimation of such a model. Empirical applications are provided to illustrate the usefulness of such a model. In addition to asymptotic properties of estimators, Monte Carlo studies provide evidence on finite sample performance of the estimation methods.
Deriving Value from Social Commerce Networks
, 2008
"... Social commerce is an emerging trend in which sellers are connected in online social networks, and where sellers are individuals instead of firms. This paper examines the economic value implications of a social network between sellers in a large online social commerce marketplace. In this marketpl ..."
Abstract

Cited by 8 (0 self)
 Add to MetaCart
Social commerce is an emerging trend in which sellers are connected in online social networks, and where sellers are individuals instead of firms. This paper examines the economic value implications of a social network between sellers in a large online social commerce marketplace. In this marketplace each seller creates his or her own shop, and network ties between sellers are directed hyperlinks between their shops. Three questions are addressed: (i) Does allowing sellers to connect to one another create value (i.e., increase sales), (ii) what are the mechanisms through which this value is created, (iii) how is this value distributed across sellers in the network and how does the position of a seller in the network (e.g., its centrality) influence how much it benefits or suffers from the network? We find that: (i) allowing sellers to connect generates considerable economic value; (ii) the network’s value lies primarily in making shops more accessible to customers browsing the marketplace (the network creates a “virtual shopping
A SpatioTemporal Model of House Prices in the US
, 2008
"... This paper provides an empirical analysis of changes in real house prices in the US using State level data. It examines the extent to which real house prices at the State level are driven by fundamentals such as real per capita disposable income, as well as by common shocks, and determines the speed ..."
Abstract

Cited by 7 (2 self)
 Add to MetaCart
This paper provides an empirical analysis of changes in real house prices in the US using State level data. It examines the extent to which real house prices at the State level are driven by fundamentals such as real per capita disposable income, as well as by common shocks, and determines the speed of adjustment of real house prices to macroeconomic and local disturbances. We take explicit account of both cross sectional dependence and heterogeneity. This allows us to find a cointegrating relationship between real house prices and real per capita incomes with coefficients (1; 1) , as predicted by the theory. We are also able to identify a significant negative effect for a net borrowing cost variable, and a significant positive effect for the State level population growth on changes in real house prices. Using this model we then examine the role of spatial factors, in particular the effect of contiguous states by use of a weighting matrix. We are able to identify a significant spatial effect, even after controlling for State specific real incomes, and allowing for a number of unobserved common factors. We do, however, find evidence of departures from long run equilibrium in the housing markets in a number of States
Rate Transformations and Smoothing
"... Core support for the development of these materials was provided through ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
Core support for the development of these materials was provided through
A Spatial Econometric Approach to the Economics of SiteSpecific Nitrogen Management in Corn Production
"... Spatial technologies such as GPS and GIS increasingly form the basis for sitespecific management in crop production. This paper assesses the contribution of an explicit spatial econometric methodology in the estimation of crop yield functions that are used to optimize fertilizer application. The sp ..."
Abstract

Cited by 3 (1 self)
 Add to MetaCart
Spatial technologies such as GPS and GIS increasingly form the basis for sitespecific management in crop production. This paper assesses the contribution of an explicit spatial econometric methodology in the estimation of crop yield functions that are used to optimize fertilizer application. The specific case study is for Nitrogen (N) application to corn production in Argentina, where the implementation of variable rate technology (VRT) requires methods that use inexpensive information and that focus on the inputs and variability common to Argentine growing areas. The objective of the paper is to assess the economic value of the application of spatial regression analysis to yield monitor data as a means to optimize variable rate fertilizer strategies. The data in the case study are from onfarm trials with a uniform N rate along strips and a randomized complete block design to estimate sitespecific crop response functions. Spatial autocorrelation and spatial heterogeneity are taken into account in regression estimation of N response functions by landscape position, in the form of both a spatial autoregressive error structure and groupwise heteroskedasticity. Both uniform rate and VRT returns are computed from a