Is the Retail Gasoline Market Local or National?

This paper studies the effect of station density on prices in the retail gasoline market in the Czech Republic. We estimate the impact of the number of competing stations in various driving-distance ranges around each station on prices. We find that station density has a negative effect on prices; the effect decreases with distance and is statistically significant up to six kilometers. This suggests that the retail gasoline market is local rather than national.     

Regulation of Labour Markets in the European Union

EU regulation of labour markets under the Social Charter and Protocol to improve 'employment rights' may appear loudable but can prove costly for firms. Mandates will probably make the unskilled more difficult to employ.     

LABOUR SUPPLY ESTIMATION AND PUBLIC POLICY

Abstract. Economists devote considerable energies towards refining their econometric techniques to overcome difficulties connected with conducting empirical research. Despite advances in technique. it is not clear whether further refinement in this direction is worthwhile for policy purposes. It may be that no further amount of statistical adjustment of inadequate data will increase understanding, and that better data is simply necessary to add to our knowledge. But rarely is sufficient credit paid to new forms of data. In short, econometric technique is emphasized to the neglect of data innovation, as if new data were merely lying about waiting for an ingenious suggestion for use. This paper surveys advances of the last twenty five years in estimating labour supply for policy purposes with a view towards appreciating the relative contribution of both improvements in econometric technique as well as developments of new data.
After briefly detailing the key parameters which economists have sought to estimate, we describe the early 'first generation' research (circa 1970), which is plagued by problems of unobservable variables, measurement errors, truncation and selectivity bias, and non linear budget constraints. 'Second generation' research constitute attempts to resolve one or more of these difficulties, and the respective contribution of econometric technique and new data is acknowledged and assessed, including the contribution of data generated by large scale social experiments in which participants are randomly assigned to different guaranteed income plans and their labour supply behaviour measured.     

Reinterpreting the performance of immigrant wages from panel data

Immigrants differ from the native born in terms of unobserved factors, such as motivation, and observed factors, including those related to the interruption of labour market activity and earning capacity, which may bias estimates of immigrant integration. Using panel data from the Survey of Labour and Income Dynamics, we show that using potential experience, rather than actual experience, exaggerates estimates of the disruption and recovery caused by immigration. More importantly, we find support for omitted variables bias, arising from unobserved fixed effects. Instrumental variable estimates for both pooled and separate samples of immigrant and native born men demonstrate a wage disadvantage for immigrants upon entry that persists through their lifetime. Standard estimates of a modest wage advantage for the children of immigrants also suffer from omitted variables bias arising from unobservables. Contrary to most of the literature to date, our instrumental variable estimates which allow for unobservable fixed effects suggest that immigrants never catch up to otherwise comparable native born workers, but their children do just as well. We would like to thank Statistics Canada for permitting access to the data and solving associated technical problems, the Prairier Centre for Research on Immigration and Integration for financial assistance, and Peter Schnabl for excellent research assistance. An earlier version of this paper was presented to the 10th International Conference on Panel Data in Berlin, July 5–6, 2002. The authors take sole responsibility for errors, omissions and interpretation of the data.     

Making the ‘Invisible’ Visible: Redevelopment‐induced Displacement of Migrants in Shenzhen,China

Gentrification in China is intertwined with urban redevelopment, which causes the large‐scale displacement of rural–urban migrants from ‘villages in the city’ (ViCs). Because of the informality of ViCs, migrant renters have very insecure tenancy and during redevelopment they are treated as a negligible (‘invisible’) social group. As they are very difficult to locate after displacement, they are also literally invisible to researchers. To make the invisible visible, this study traced a sample of displaced migrants from Huangbeiling village in Shenzhen. The focus was on the displacement process and on identifying the consequences for the displaced. We found various forms of displacement during the redevelopment process. Nearby ViCs were prioritized by displaced migrants to minimize as much utility loss as possible. However, they generally suffer from decreased proximity, increased living costs, and the loss of social networks and job opportunities. Remarkably, some choose to return to the gentrifying village, enduring displacement in situ caused by increasing rents, drastic physical neighbourhood changes and declining liveability, in exchange for retaining their original social and economic networks. Large‐scale urban redevelopment is causing the rapid shrinkage of informal housing. Recognizing and addressing the housing needs of this impoverished social group is a matter of urgency.     

Pricing European Options by Numerical Replication: Quadratic Programming with Constraints

The paper considers a regression approach to pricing European options in an incomplete market. The algorithm replicates an option by a portfolio consisting of the underlying security and a risk-free bond. We apply linear regression framework and quadratic programming with linear constraints (input = sample paths of underlying security; output = table of option prices as a function of time and price of the underlying security). We populate the model with historical prices of the underlying security (possibly massaged to the present volatility) or with Monte Carlo simulated prices. Risk neutral processes or probabilities are not needed in this framework.     

Financial prediction with constrained tail risk

A new class of asymmetric loss functions derived from the least absolute deviations or least squares loss with a constraint on the mean of one tail of the residual error distribution, is introduced for analyzing financial data. Motivated by risk management principles, the primary intent is to provide “cautious” forecasts under uncertainty. The net effect on fitted models is to shape the residuals so that on average only a prespecified proportion of predictions tend to fall above or below a desired threshold. The loss functions are reformulated as objective functions in the context of parameter estimation for linear regression models, and it is demonstrated how optimization can be implemented via linear programming. The method is a competitor of quantile regression, but is more flexible and broader in scope. An application is illustrated on prediction of NDX and SPX index returns data, while controlling the magnitude of a fraction of worst losses.     

Decomposing Local: A Conjoint Analysis of Locally Produced Foods

Increasingly, foods are marketed as "locally grown." We use stated preference data from a choice-based conjoint instrument to address two issues surrounding consumer demand for locally produced goods: (1) what is the geographical extent of "local," and (2) is the value consumers place on "local" production distinct from other factors that are often confounded with locally produced foods such as farm size and product freshness? We find our subjects place similar value on products produced "in state" and "nearby" and that consumers' willingness to pay for local production is independent from values associated with product freshness and farm size.