Simulated economic impacts in applied trade modelling: A comparison of tariff aggregation approaches

This paper assesses the performance of two recently developed tariff aggregators in reducing tariff aggregation bias by analysing Swiss beef market liberalisation scenarios. Specific relevant sources of bias are addressed: substitution effects on import demand, Tariff Rate Quotas and overprotection in tariffs. The aggregators are linked to a global large-scale partial equilibrium model and benchmarked against a standard aggregator. The choice of the aggregation method shows considerable effects on simulated economic impacts, specifically if the dispersion in tariffs or tariff cuts is large. A large bias is revealed in simulated gains from trade liberalisation using the standard aggregator. The impacts on traded quantities are found to be overestimated, while price and welfare effects can be higher or lower by switching to alternative aggregation methods. By reducing aggregation bias and depicting negotiated tariff schedules more directly, the proposed aggregators enhance the contribution of trade modelling to evidence-based policy making.     

Who votes for public environmental goods in California?: Evidence from a spatial analysis of voting for environmental ballot measures

Voting referenda provide direct evidence of the demand for public goods. A number of previous studies have used referenda to analyze the support for public environmental goods. These studies have used aggregate data from large jurisdictional units (usually counties) and summary income measures such as the mean or median, and have usually found that higher income areas offer greater support for environmental propositions. We examine environmental referenda voting in California using census block group data, spatial dependence controls, and detailed income distribution data. We find that household income has a negative marginal effect on environmental referenda voting for most of the income range when using census block data. In addition, controls for spatial dependence significantly reduce the magnitude of most coefficients. This suggests that OLS estimates of referenda determinants are biased. We also show that county level data may be subject to severe aggregation bias and might not be appropriate for referenda studies.     

Inferring Transactions from Financial Statements*

In this paper, we embed the double entry accounting structure in a simple belief revision (estimation) problem. We ask the following question: Presented with a set of financial statements (and priors), what is the reader's “best guess” of the underlying transactions that generated these statements? Two properties of accounting information facilitate a particularly simple closed form solution to this estimation problem. First, accounting information is the outcome of a linear aggregation process. Second, the aggregation rule is double entry.     

Biases in demand analysis due to variation in retail distribution

Aggregate demand models typically assume that consumers choose between all available products. Since consumers may be unwilling to search across every store in a given market for a particular item, this assumption is problematic when product assortments vary across stores. Using supermarket scanner data for five product categories we demonstrate that approximately one third of products have limited retail distribution, which account for one fourth of dollar sales. Monte Carlo analysis demonstrates that the level of limited product availability observed in the data can significantly bias the results of aggregate demand models that incorrectly assume all consumers in a given market face the same choice set.     

Estimating dynamic response models when the data are subject to different temporal aggregation

In estimating response models using secondary data, it can happen that the observations on the variables are subject to different temporal aggregation. Estimating a dynamic model with this type of data is not straightforward, particularly when (a) estimates with good statistical properties are desired, and (b) full use of all information in the data is needed. This paper provides an overview and discussion of the various approaches to the estimation problem when independent variables are observed less frequently than the dependent variable. The superiority of one-step estimation procedures that simultaneously estimate the parameters and the missing disaggregated data points is established.Insead     

Euro area inflation persistence

This paper presents evidence on the lag between monetary policy actions and the response of inflation in the euro area as a whole as well as in some of its core countries, notably Germany, Italy and France. In line with previous findings for the US and the UK, results here show that it takes over a year before monetary policy actions have their maximum effect on inflation both in the euro area and in individual countries and that a lag of this length has existed in Europe at least since the collapse of the Bretton Woods system, despite the numerous changes in European monetary policy regime thereafter. Results based on alternative definitions of inflation persistence support these findings and indicate, if any, that transmission lags could be in fact much longer for individual countries and the euro area as a whole, although, at the country level, there is strong evidence over time of a drop in German inflation persistence and a sizeable shift in the mean of inflation – particularly in Italy and France. An examination based on results from this paper reveals that euro area inflation persistence could well be an intrinsic phenomenon rather than a ‘statistical fluke’ due to aggregation.This research was conducted during my visit at the European Central Bank Directorate Research, as part of the Research Visitor Programme. I would like to thank Anna Maria Agresti for providing individual country data from the macroeconomic database of the Monetary Transmission Network; Alistair Dieppe for providing data from the ECB area-wide model dataset; and Michele Manna for supplying me with the area-wide M3 data for the period 1970–1980. I thank Gabriel Fagan, Frank Smets, Ignazio Angeloni, Vítor Gaspar, Michael Ehrmann, Guenter Coenen, Oreste Tristani, Tommaso Monacelli, Stephanie Schmitt-Grohe and Gerhard Ruenstler for helpful discussions during my stay at the ECB. I would also like to thank seminar participants at the ECB for their input and I am very grateful to Jeffrey Fuhrer, Edward Nelson and Kenneth West, Bernd Fitzenberger and two anonymous referees for comments on an earlier draft. Any errors and omissions are mine. The views expressed in this paper are those of the author and should not be attributed to the International Monetary Fund, its Executive Board, or its management     

Estimating firm-level and country-level effects in cross-sectional analyses: An application of hierarchical modeling in corporate disclosure studies

Researchers in the field of international accounting are often confronted with observations of firms clustered into higher-level units such as countries. Using data from a corporate disclosure study including 797 firm observations from 34 countries, we demonstrate that the inferences obtained from the most commonly used Ordinary Least Square (OLS) test, which pools the firm and country data either under the disaggregation or aggregation approach, are problematic and misleading. To overcome the methodological limitation, we subsequently employ hierarchical modeling to simultaneously estimate both firm-level (within-country) and country-level (cross-country) disclosure determinants. We find that the clustering effects are significant in almost all firm-level variables. Once such effects are adjusted, only three firm-specific variables are significantly associated with corporate disclosure. Evidence provided by this study has important implications for most international accounting studies conducted in cross-level contexts.     

中国金融集聚水平的现状与影响因素探析

金融集聚作为产业集聚的一种表现形式,在我国呈现出在曲折中缓慢上升的趋势,而且这种趋势有向东部发达地区延伸的迹象。为验证并进一步探究影响这种趋势的相关因素,一方面,引入空间基尼系数、HI指数和行业集中度三种测度方法,对我国金融集聚的现状作出分析;另一方面,通过回归分析考察我国金融集聚与工业化程度、货币化程度和经济发展水平之间的关系,认为经济的货币化程度和经济发展水平是影响这种集聚趋势的重要因素。     

The information content of regional employment data for forecasting aggregate conditions

We consider whether disaggregated data enhance the efficiency of aggregate employment forecasts. We find that incorporating spatial interaction into a disaggregated forecasting model lowers the out-of-sample mean squared error from a univariate aggregate model by 70% at a two-year horizon.