Empirics and the Pollution Haven Hypothesis (PHH)Empirical questions related to PHHWhat is a statistical model?More details on statistical model (a.k.a. “regression equation”)Alternatives for addressing question “Does trade harm the environment?”The empirical evidenceEarly evidenceInterpretation of these resultsEarly studies of trade effect of pollution control costsThe relation between trade flows and measures of environmental stringencyStatistical reasons why these studies might incorrectly reject PHHWhat do we mean by speaking of the “demand function” and the “supply function” for pollution?The optimal pollution tax (the price of a unit of pollution) is given by the intersection of the supply and demand curves for pollutionExample 1: statistical model correctly identifies a relation between pollution control costs and tradeA higher tax reduces firms’ level of pollution (left panel), increasing their production costs, causing the supply curve to shift in (dotted curve in right panel)Example 2: statistical model understates relation between abatement costs and trade (or gets sign wrong), due to an omitted explanatory variable that is incorporated into the error term – leading to correlation between the pollution tax and the error (a form of endogeneity)Increase in factor shifts out demand curve for pollution (dotted curve, left panel), raising the pollution tax. By assumption, the higher supply of factor decreases marginal cost of dirty good, even with the higher tax, so supply function of dirty good shifts out (dotted curve in right panel). A higher pollution tax is correlated with higher supply of dirty good. Dashed curve right panel shows the supply effect of increase in factor, absent the increase in taxExample 3: statistical model overstates relation between abatement costs and trade, due to omitted explanatory variableSome recent statistical evidenceRelated (older) trade and environment studiesSummarySummary, continuedAnd most importantly…Empirics and the Pollution Haven Hypothesis (PHH)November 10, 2007Empirical questions related to PHH•Do investment flows respond to differences in environmental standards?•Has trade liberalization increased pollution intensity in developing countries?•Have tighter standards in developed countries led to loss in pollution-intensive industries?•The literature does not attempt to determine whether countries use environmental policies that are too weak, in order to attract investment or increase market share of dirty goods. That is, the literature does not attempt to uncover the motive of environmental policy.What is a statistical model?•We are interested in relation between net exports and pollution control costs.•We know that net exports depend on other variables (e.g. supply of factors – remember the HOS model and Rybczynski theorem)•If we have data on these variables we can estimate a relation between exports and pollution control costs, while “controlling” for other variables (e.g. supply of factors).•We are (usually) interested in sign and magnitude of coefficient on pollution control costs, and on whether the coefficient is statistically significant.More details on statistical model (a.k.a. “regression equation”)•The subscript i identifies the country and the subscript t identifies the time period. For the PPH, the dependent variable y is a measure of exports of the dirty good, the explanatory variable x is a measure of pollution control costs, z contains other explanatory variables, called “control variables” (e.g. factor endowments for the PHH); e is the equation “error”, a composite of factors that we do not observe, but which affect the dependent variable, and a component that takes into account the inherent randomness of the process.•The statistical problem is to estimate the parameters, particularly beta, and determine whether it is positive and statistically different than 0.•There are many technical problems: missing data, data with measurement errors, correlation between error and explanatory variables, misspecification of model…., ,i t i t it ity x z eb g= + +Alternatives for addressing question “Does trade harm the environment?”•Theory, i.e. try to determine the likely relation between trade and the environment using logic. Theory helps you “think clearly” but is inconclusive.•Case studies, i.e. finding examples where the relation appears positive or negative. These are useful, but they leave you wondering how representative the case studies are.•Statistical models – these have the advantage of being based on widely accepted principles, but the data seldom exactly conforms to the statistical assumptions.The empirical evidence•Early studies use US data to categorize industries into dirty and clean sectors (based on emissions per $ of output, or per employee, or on abatement costs).•The statistical exercise looks for link between dirty and clean good trends in production or export (share) and country characteristics such as income, income growth, and openness.•Are developing countries “moving toward” dirty industries?•This type of exercise ignores possible changes in technique -- it assumes that changes in composition translate directly into changes in pollution. Also ignores other explanatory values, such as factor endowments.Early evidence•Early research found that a rise in environmental control costs in North was positively correlated with increases in dirty good share of exports from developing countries, and decreases in dirty good share of exports from rich countries. •The Lucas and Wheeler study found that toxic releases per unit of output (measured by GNP) fell as countries became richer, due to changes in composition. Poorer countries had the largest increases in toxic intensity.•Birdsall and Wheeler found that pollution intensity increased most rapidly in Latin American countries after OECD pollution regulation became stricter.Interpretation of these results•These findings are consistent with PHH, but are also consistent with an explanation based on changes in factor endowments (capital accumulation). •Evidence for the importance of capital accumulation: (i) Over 90% of dirty good production in 1988 was in OECD countries, suggesting that location of dirty good production reflects more than weak environmental regulation. (ii) If stricter environmental policies in rich countries were responsible for
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