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This paper estimates the effect of environmental regulation on industry location and compares it with other determinants of location such as agricultural, education and R&D country characteristics. The analysis is based on a general empirical trade model that captures the interaction between country and industry characteristics in determining industry location. The Johnson-Neyman technique is used to fully explicate the nature of the conditional interactions. The model is applied to data on 16 manufacturing industries from 13 European countries. The empirical results indicate that the pollution haven effect is present and that the relative strength of such an effect is of about the same magnitude as other determinants of industry location. A significant negative effect on industry location is observed only at relatively high levels of industry pollution intensity., Replaced with revised version of paper 02/20/09.

This is a revised version of a previous working paper, of the same name, which incorporates corrections to errors in our estimates of TFP growth. This paper examines major privately-owned British railway companies before World War I. Quantitative evidence is presented on return on capital employed, total factor productivity growth, cost inefficiency, and speed of passenger services. There were discrepancies in performance across companies but ROCE and TFP typically fell during our period. Cost inefficiency rose before 1900 but then was brought under control as a profits collapse loomed. Without the discipline of either strong competition or effective regulation, managerial failure was common. This sector is an important qualification to the conventional wisdom that late-Victorian Britain did not fail.

This paper revisits the issue of the productivity performance of pre-World War I Britain’s railway system with an improved dataset and with modern time-series econometrics. We find a slowdown in TFP growth between 1850 and 1870, after which it stabilized at about 1.1%. An analysis of company-level productivity rejects the claims that there was a regulation-induced revival of productivity performance in the railway sector after 1900 but, on the other hand, it supports the claim that there was some managerial failure during the period.

This paper uses a stochastic cost frontier model to investigate the efficiency of Britain’s private railways during the period 1893-1912. We find that there was substantial inefficiency in the industry with no sign of reduction over time. Our main conclusion is that principal agent problems were pervasive in railway management at this time. Our results suggest that private ownership per se is not sufficient to promote efficiency in the railway industry; it should be supported by competition for franchises and price-capping regulation as in the 1990s.

This paper explores the location of industry in pre-World-War-I Britain using a model that takes account both of factor endowment and also of new economic geography influences. Broadly speaking, the pattern of industrial location in this period was quite persistent and regional specialization changed little. The econometric results show that factor endowments had much stronger effects than proximity to markets, although the latter was an attraction for industries with large plant size. Overall, falling transport costs had relatively little effect on industrial location at a time when proximity to natural resources, notably coal, mattered most.

Is there a case to be made for preferential treatment of the exposed sector in an economy when compliance to an aggregate emissions constraint induced by an international environmental agreement is mandatory? This question is being debated in many countries, including The Netherlands, in the context of the implementation of the Kyoto protocol. We address this issue in a general equilibrium framework in this paper, and theoretically cover several market structures, including perfect competition, oligopoly and the large country case. Our main finding is that in many circumstances preferential treatment is not warranted from the point of view of maximizing social welfare.

The potential relationship between domestic environmental regulation and internationalcompetitiveness has evoked various speculations. The common neoclassical train of thought is thatstrict environmental regulation is detrimental to the competitiveness of industry, and that itinduces phenomena such as ecological dumping, ecological capital flight, and regulatory 'chill' inenvironmental standards. A different view is that strict environmental regulation triggers industry'sinnovation potential, and subsequently increases its competitiveness. The impact of environmentalregulation on competitiveness has been analyzed in terms of international capital movements, newfirm formation, and international trade. This paper focuses on a statistically rigorous analysis ofinternational trade studies, using a technique that is known as meta-analysis. The paper presentsa statistically supported evaluation of the literature, in order to assess what the main conclusionsregarding the relationship between environmental regulation and competitiveness are when itcomes to studies on international trade flows. The synthesis of the literature is subsequently usedto present guidelines for future primary research in this area.

This paper analyses empirically the extent to which environmental regulation influences production location in the pig industry. The analysis is based on a general empirical location model that captures interactions between region and sector characteristics in determining production location, and data on pig production in 43 European regions. We find that while environmental regulation may not have a measurable effect on the EU pig industry location per se, it is a strong influence on the sectoral composition of the industry. Relatively highly-polluting sectors of the pig industry are attracted to relatively lax jurisdictions which become pollution-havens (hotspots of hog waste).

This paper estimates the effect of environmental regulation on industry location and compares it with other determinants of location such as agricultural, education and R&D country characteristics. The analysis is based on a general empirical trade model that captures the interaction between country and industry characteristics in determining industry location. The Johnson-Neyman technique is used to fully explicate the nature of the conditional interactions. The model is applied to data on 16 manufacturing industries from 13 European countries. The empirical results indicate that the pollution haven effect is present and that the relative strength of such an effect is of about the same magnitude as other determinants of industry location. A significant negative effect on industry location is observed only at relatively high levels of industry pollution intensity. © The Author(s) 2009.