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Using a firm level dataset from four regions of Russia covering 1996/97, an investigation was carried out into how the surplus created within the firm is divided between profits and wages. An efficient bargaining framework based on the work of Svejnar (1986) is employed which takes into account the alternative wage or outside option available to employees in the firm as well as the value added per employee. Statistical differences in the share of the surplus taken by employees employed in state, private and mixed forms of firms are found. In addition, the results prove sensitive to the presence of outliers and influential observations. A variety of diagnostic methods are employed to identify these influential observations and robust methods are employed to lessen the influence of them. Whereas in practice some of the diagnostic and robust methods utilised proved incapable of identifying or accommodating the gross outlier(s) in the data, the more successful methods included robust regression, Winsorising, the Hadi and Siminoff algorithm, Cook's Distance and Covratio.

This paper uses a "local average treatment effect" (LATE) framework in an attempt to disentangle the separate effects of criminal and noncriminal gun prevalence on violence rates. We first show that a number of previous studies have failed to properly address the problems of endogeneity, proxy validity, or heterogeneity in criminality. We demonstrate that the time series proxy problem is severe; previous panel data studies have used proxies that are essentially uncorrelated in time series with direct measures of gun relevance. We adopt instead a cross-section approach: we use U.S. county-level data for 1990, and we proxy gun prevalence levels by the percent of suicides committed with guns, which recent research indicates is the best measure of gun levels for cross-sectional research. We instrument gun levels with three plausibly exogenous instruments: subscriptions to outdoor sports magazines, voting preferences in the 1988 Presidential election, and numbers of military veterans. In our LATE framework, the estimated impact of gun prevalence is a weighted average of a possibly negative impact of noncriminal gun prevalence on homicide and a presumed positive impact of criminal gun prevalence. We find evidence of a significant negative impact, and interpret it as primarily "local to noncriminals", i.e., primarily determined by a negative deterrent effect of noncriminal gun prevalence. The beneficiaries of the reduced level of violence may include substantial numbers of (urban) criminals, the murders of whom decrease via spillovers from noncriminal gun prevalence. -- Crime ; homicide ; gun levels ; endogeneity

This paper uses a local average treatment effect (LATE) framework in an attempt to disentangle the separate effects of criminal and noncriminal gun prevalence on violence rates. We first show that a number of previous studies have failed to properly address the problems of endogeneity, proxy validity, or heterogeneity in criminality. We demonstrate that the time series proxy problem is severe; previous panel data studies have used proxies that are essentially uncorrelated in time series with direct measures of gun relevance. We adopt instead a cross-section approach: we use U.S. county-level data for 1990, and we proxy gun prevalence levels by the percent of suicides committed with guns, which recent research indicates is the best measure of gun levels for cross-sectional research. We instrument gun levels with three plausibly exogenous instruments: subscriptions to outdoor sports magazines, voting preferences in the 1988 Presidential election, and numbers of military veterans. In our LATE framework, the estimated impact of gun prevalence is a weighted average of a possibly negative impact of noncriminal gun prevalence on homicide and a presumed positive impact of criminal gun prevalence. We find evidence of a significant negative impact, and interpret it as primarily local to noncriminals, i.e., primarily determined by a negative deterrent effect of noncriminal gun prevalence. The beneficiaries of the reduced level of violence may include substantial numbers of (urban) criminals, the murders of whom decrease via spillovers from noncriminal gun prevalence.