Bias in returns to tenure when firm wages and employment comove: A quantitative assessment and solution

It is well known that, unless worker-firm match quality is controlled for, returns to firm tenure (RTT) estimated directly via reduced form wage (Mincer) equations will be biased. In this paper we show that even if match quality is properly controlled for there is a further pervasive source of bias, namely the co-movement of firm employment and firm wages. In a simple mechanical model where human capital is absent and separation is exogenous we show that positively covarying shocks (either aggregate or firm level) to firms employment and wages cause downward bias in OLS regression estimates of RTT. We show that the long established procedures for dealing with "traditional" RTT bias do not circumvent the additional problem we have identified. We argue that if a reduced form estimation of RTT is undertaken, firm-year fixed effects must be added in order to eliminate this bias. Estimates from two large panel datasets from Portugal and Germany show that the bias is empirically important. Adding firm-year fixed effects to the regression increases estimates of RTT in the two respective countries by between 3.5% and 4.5% of wages at 20 years of tenure over 80% (50%) of the estimated RTT level itself. The results extend to tenure correlates used in macroeconomics such as the minimum unemployment rate since joining the firm. Adding firm-year fixed effects changes estimates of these effects also.

Simulating Wages and House Prices Using the NEG

The paper incorporates house prices within an NEG framework leading to the spatial distributions of wages, prices and income. The model assumes that all expenditure goes to firms under a monopolistic competition market structure, that labour efficiency units are appropriate, and that spatial equilibrium exists. The house price model coefficients are estimated outside the NEG model, allowing an econometric analysis of the significance of relevant covariates. The paper illustrates the methodology by estimating wages, income and prices for small administrative areas in Great Britain, and uses the model to simulate the effects of an exogenous employment shock.

The effects of agglomeration on wages: evidence from the micro-level

This paper estimates individual wage equations in order to test two rival non-nested theories of economic agglomeration, namely New Economic Geography (NEG), as represented by the NEG wage equation and urban economic (UE) theory , in which wages relate to employment density. The paper makes an original contribution by evidently being the first empirical paper to examine the issue of agglomeration processes associated with contemporary theory working with micro-level data, highlighting the role of gender and other individual-level characteristics. For male respondents, there is no significant evidence that wage levels are an outcome of the mechanisms suggested by NEG or UE theory, but this is not the case for female respondents. We speculate on the reasons for the gender difference.

Monthly wages in the Swiss Household Panel

This paper describes the construction of monthly income from employment and self employment in the Swiss Household Panel (SHP). It documents the assumptions that have to be taken and addresses possibilities and difficulties when relating monthly income variables with the number of working hours. Finally, some descriptive statistics of the monthly wages are provided from 1999 to 2008. These show a high correlation of wages across the years, which is higher than correlation from yearly wages. This underlies the suitability of these variables on monthly wages for labour market research with the SHP. Median and average hourly wages have increased slightly from 2002 to 2008. The inequality of wages has remained stable for the total population.

The impact of agglomeration effects and accessibility on wages

This paper contributes to the empirical literature on the effects of agglomeration and road accessibility on productivity of firms by looking at the case of Spain. We approach productivity indirectly by using individual wages allocated at the NUTS III level. We use a repeated cross-section of individual micro-data for the years 1995, 2002 and 2006. The availability of interprovincial travel time data for each of the three years allows controlling for transport improvements over the period by using a market potential variable. Additionally, agglomeration is approached by employment density and we control for localization economies, human capital externalities and a large set of individual and workplace characteristics. Estimating by instrumental variables, our results show a positive and significant effect of market accessibility on wages and non linear effect for employment density.

How Wages and Employment Adjust to Trade Liberalization: Quasi-Experimental Evidence from Austria

We study the response of regional employment and nominal wages to trade liberalization, exploiting the natural experiment provided by the opening of Central and Eastern European markets after the fall of the Iron Curtain in 1990. Using data for Austrian municipalities, we examine differential pre- and post-1990 wage and employment growth rates between regions bordering the formerly communist economies and interior regions. If the "border regions" are defined narrowly, within a band of less than 50 kilometers, we can identify statistically significant liberalization effects on both employment and wages. While wages responded earlier than employment, the employment effect over the entire adjustment period is estimated to be around three times as large as the wage effect. The implied slope of the regional labor supply curve can be replicated in an economic geography model that features obstacles to labor migration due to immobile housing and to heterogeneous locational preferences.

Discrepancies between Aedes aegypti identification in the field and in the laboratory after collection with a sticky trap

Currently, sticky traps are regularly employed to assist in the surveillance of Aedes aegypti infestation. We tested two alternative procedures for specimen identification performed by local health agents: directly in the field, as recommended by certain manufacturers, or after transportation to the laboratory. A total of 384 sticky traps (MosquiTRAP) were monitored monthly during one year in four geographically representative Brazilian municipalities. When the same samples were inspected in the field and in the laboratory, large differences were noted in the total number of mosquitoes recorded and in the number of specimens identified as Ae. aegypti by both procedures. Although field identification has the potential to speed vector surveillance, these results point to uncertainties in the evaluated protocol.

Employment and Wages Covered by Unemployment Insurance, Final County Data, Third Quarter, 2003

Third Quarterly County information for Census of Employment & Wages - County

Employment and Wages Covered by Unemployment Insurance, Final Statewide Data, Third Quarter, 2003

Third Quarterly County information for Census of Employment & Wage, Statewide

Employment and Wages Covered by Unemployment Insurance, Final County Data, Fourth Quarter, 2003

Fourth Quarterly County information for Census of Employment & Wage, County

Employment and Wages Covered by Unemployment Insurance, Final Statewide Data, Fourth Quarter, 2003

Fourth Quarterly County information for Census of Employment & Wage, Statewide

Quarterly Census of Employment and Wages, Final County Data, First Quarter, 2004

First Quarterly County information for Census of Employment & Wage, County

Quarterly Census of Employment and Wages, Final Statewide Data, First Quarter, 2004

First Quarterly County information for Census of Employment & Wage, Statewide

Quarterly Census of Employment and Wages, Preliminary County Data, Second Quarter, 2004

Second Quarterly County information for Census of Employment & Wage, County

Quarterly Census of Employment and Wages, Preliminary Statewide Data, Second Quarter, 2004

Second Quarterly County information for Census of Employment & Wage, Statewide