The effect of physician advice on alcohol consumption: count regression with an endogenous treatment effect

Although there are encouraging trends, alcohol abuse continues to be a significant public health problem. Econometric studies of alcohol demand have yielded a great deal of information for alcohol abuse prevention policy. These studies suggest that higher alcohol taxes and stricter drunk‐driving policies can reduce heavy drinking and drunk driving. In this paper we explore the role physician advice plays in the campaign to prevent alcohol‐related problems. Compared to alcohol taxation, physician advice is a more precisely targeted intervention that does not impose extra costs on responsible drinkers. Compared to the resource costs of arresting, processing, and punishing drunk drivers, physician advice may be a lower‐cost intervention. To provide a basis for alcohol policy analysis, we use an alcohol demand framework to test whether physician‐provided information about the adverse consequences of alcohol abuse shifts demand to more moderate levels. There are three aspects of our alcohol demand model that complicate the estimation: (1) the dependent variable is non‐negative (it is a count variable—number of drinks consumed); (2) a non‐trivial number of sample observations have zero values for the dependent variable; and (3) because the data we use is non‐experimental, the treatment variable indicating receipt of advice from a physician may be endogenous. We implement an estimation method that is specifically designed to deal with these three complicating factors. Our results show that advice has a substantial and significant impact on alcohol consumption by males with hypertension, and that failing to account for the endogeneity of advice masks this result. Copyright © 2001 John Wiley & Sons, Ltd.     

Equilibrium Exchange Rates in Transition Economies: Taking Stock of the Issues*

Abstract. In this paper, we present an overview of a number of issues relating to the equilibrium exchange rates of transition economies of the former soviet bloc. In particular, we present a critical overview of the various methods available for calculating equilibrium exchange rates and discuss how useful they are likely to be for the transition economies. Amongst our findings is the result that the trend appreciation usually observed for the exchange rates of these economies is affected by factors other than the usual Balassa–Samuelson effect, such as the behaviour of the real exchange rate of the open sector and regulated prices. We then consider three main sources of uncertainty relating to the implementation of an equilibrium exchange rate model, namely: differences in the theoretical underpinnings, differences in the econometric estimation techniques, and differences relating to the time‐series and cross‐sectional dimensions of the data. The ensuing three‐dimensional space of real misalignments is probably a useful tool in determining the direction of a possible misalignment rather than its precise size.     

ECONOMETRIC MODELS OF ASYMMETRIC PRICE TRANSMISSION

Abstract In this paper, we review the existing empirical literature on price asymmetries in commodities, providing a way to classify and compare different studies that are highly heterogeneous in terms of econometric models, type of asymmetries and empirical findings. Relative to the previous literature, this paper is novel in several respects. First, it presents a detailed and updated survey of the existing empirical contributions on price asymmetries in the transmission mechanism linking input prices to output prices. Second, this paper presents an extension of the traditional distinction between long‐run and short‐run asymmetries to new categories of asymmetries, such as: contemporaneous impact, distributed lag effect, cumulated impact, reaction time, equilibrium and momentum equilibrium adjustment path, regime effect, regime equilibrium adjustment path. Each empirical study is then critically discussed in the light of this new classification of asymmetries. Third, this paper evaluates the relative merits of the most popular econometric models for price asymmetries, namely autoregressive distributed lags, partial adjustments, error correction models, regime switching and vector autoregressive models. Finally, we use the meta‐regression analysis to investigate whether the results of asymmetry tests are not model‐invariant and find which additional factors systematically influence the rejection of the null hypothesis of symmetric price adjustment. The main results of our survey can be summarized as follows: (i) each econometric model is specialized to capture a subset of asymmetries; (ii) each asymmetry is better investigated by a subset of econometric models; (iii) the general significance of the F test for asymmetric price transmission depends mainly on characteristics of the data, dynamic specification of the econometric model, and market characteristics. Overall, our empirical findings confirm that asymmetry, in all its forms, is very likely to occur in a wide range of markets and econometric models.     

How did structural reform influence inflation in transition economies?

This paper empirically examines the contribution of structural reforms to reducing inflation using a panel data-set of 25 transition economies. Two econometric methodologies are applied. First, the Blundell and Bond (1998) estimator for panel data incorporating lags of the dependent variable. Second, a panel logit estimator is employed to consider the likelihood of achieving low inflation. Results highlight the importance of price and trade liberalization and the reform of credit allocation for reducing inflation, the latter being especially important for bringing inflation below 10%.     

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.     

Factor MIDAS for Nowcasting and Forecasting with Ragged‐Edge Data: A Model Comparison for German GDP*

In this article, we merge two strands from the recent econometric literature. First, factor models based on large sets of macroeconomic variables for forecasting, which have generally proven useful for forecasting. However, there is some disagreement in the literature as to the appropriate method. Second, forecast methods based on mixed‐frequency data sampling (MIDAS). This regression technique can take into account unbalanced datasets that emerge from publication lags of high‐ and low‐frequency indicators, a problem practitioner have to cope with in real time. In this article, we introduce Factor MIDAS, an approach for nowcasting and forecasting low‐frequency variables like gross domestic product (GDP) exploiting information in a large set of higher‐frequency indicators. We consider three alternative MIDAS approaches (basic, smoothed and unrestricted) that provide harmonized projection methods that allow for a comparison of the alternative factor estimation methods with respect to nowcasting and forecasting. Common to all the factor estimation methods employed here is that they can handle unbalanced datasets, as typically faced in real‐time forecast applications owing to publication lags. In particular, we focus on variants of static and dynamic principal components as well as Kalman filter estimates in state‐space factor models. As an empirical illustration of the technique, we use a large monthly dataset of the German economy to nowcast and forecast quarterly GDP growth. We find that the factor estimation methods do not differ substantially, whereas the most parsimonious MIDAS projection performs best overall. Finally, quarterly models are in general outperformed by the Factor MIDAS models, which confirms the usefulness of the mixed‐frequency techniques that can exploit timely information from business cycle indicators.     

Nonparametric methods and local‐time‐based estimation for dynamic power law distributions

This paper introduces nonparametric econometric methods that characterize general power law distributions under basic stability conditions. These methods extend the literature on power laws in the social sciences in several directions. First, we show that any stationary distribution in a random growth setting is shaped entirely by two factors: the idiosyncratic volatilities and reversion rates (a measure of cross‐sectional mean reversion) for different ranks in the distribution. This result is valid regardless of how growth rates and volatilities vary across different economic agents, and hence applies to Gibrat's law and its extensions. Second, we present techniques to estimate these two factors using panel data. Third, we describe how our results imply predictability as higher‐ranked processes must on average grow more slowly than lower‐ranked processes. We employ our empirical methods using data on commodity prices and show that our techniques accurately describe the empirical distribution of relative commodity prices. We also show that rank‐based out‐of‐sample forecasts of future commodity prices outperform random‐walk forecasts at a 1‐month horizon.     

How accurate are government forecasts of economic fundamentals? The case of Taiwan

A government’s ability to forecast key economic fundamentals accurately can affect business confidence, consumer sentiment, and foreign direct investment, among others. A government forecast based on an econometric model is replicable, whereas one that is not fully based on an econometric model is non-replicable. Governments typically provide non-replicable forecasts (or expert forecasts) of economic fundamentals, such as the inflation rate and real GDP growth rate.In this paper, we develop a methodology for evaluating non-replicable forecasts. We argue that in order to do so, one needs to retrieve from the non-replicable forecast its replicable component, and that it is the difference in accuracy between these two that matters. An empirical example to forecast economic fundamentals for Taiwan shows the relevance of the proposed methodological approach. Our main finding is that the undocumented knowledge of the Taiwanese government reduces forecast errors substantially.     

Driving sectoral sustainability via the diffusion of organizational eco‐innovations

Using insights from institutional literature, the resource‐based theory of the firm, and internationalization, we explain variations in the diffusion of organizational eco‐innovations. Studies have previously reported that the drivers of eco‐innovation are regulatory pressures, technology push, market pull, and firm factors. But relatively little attention has been paid to nontechnological forms of eco‐innovation, such as environmental management systems (EMS). Consequently, how exactly to encourage EMS adoption across sectors is still unclear. We attempt to address this question by combining sectoral panel data (2009–2014) from a number of sources in Spain. The econometric analysis reveals that environmental policy is driving the adoption of ISO 14001 largely due to differences across sectors in energy and pollution intensity. In addition, the adoption of ISO 9001 increases the use of ISO 14001 in industry because of complementarities between the two systems. Third, in highly internationalized sectors, firms adopt a greater amount of ISO 14001.     

Tests of the money-output relation using disaggregated data

Either anticipated or unanticipated money affects output in fourteen of twenty U.S. manufacturing industries. In most of these instances, however, Akaike's final prediction error criterion indicates that money enters an industry's output equation with lags of three months or less. For just two industries, tobacco manufacturing and textile mill products, are there clear indications that money is not neutral at extended lags. Each of these industries is concentrated in one or two states suggesting that monetary policy may affect output through a regional credit channel.     

Multisectoral econometric models of the centrally planned economies and the disequilibria

The paper provides a systematic analysis of the properties of large econometric macro models built for the Centrally Planned economies of the '70s and '80s. A specific typology of macro models is introduced, distinguishing between the demand and quasi-demand determined systems on the one hand and the supply and quasi-supply determined systems on the other, and also between complete and incomplete models specifying only one side of economic activities (i.e. generating either demand or supply). It is shown that, under the command type economy, the incomplete, fully supply determined systems prevailed, generating production and showing its allocation. The economic reforms of the '80s, which aimed at a slow transition towards market economies, brought about a tendency towards constructing complete quasi-supply determined systems (especially for Poland and the CSRS). Since, in principle, they were built for shortage economies, the model builders had to allow for unobservables (final and intermediate demand, capacity utilization) and, on the other hand, for an increasing role of the financial phenomena (including prices) and financial policy instruments. A summary of the applications of macro models in forecasting and policy simulations is provided and new tendencies associated with regaining economic equilibria and approaching the market mechanisms emerging in the period of transition are shown.This is a revised and extended version of our paper delivered at the Project LINK Meeting in Paris, 1989 (see W. Welfe 1989b), which made use of our earlier publication (W. Welfe 1988).     

Is econometrics useful for private policy making? A case study of replacement policy at an auto rental company

The goal of this paper is to illustrate the potential usefulness of econometrics as a tool to assist private policy makers. We provide a case study and detailed econometric analysis of the automobile replacement policy adopted by a large car rental company. Unlike public policy making–where the benefits from using econometric models and “science-based” approaches to policy making are hard to quantify because the outcomes of interest are typically subjective quantities such as “social welfare”–in the case of firms there is an objective, easily quantifiable criterion for judging whether policy A is better than policy B: profits. We introduce and estimate an econometric model of the rental histories of individual cars in the company’s fleet. Via stochastic simulations, we show that the model provides a good approximation to the company’s actual operations. In particular, the econometric model is able to reproduce the extraordinarily high rates of return that the company obtains on its rental cars, with average internal rates of return between purchase and sale of approximately 50%. However, the econometric model can simulate outcomes under a range of counterfactual vehicle replacement policies. We use the econometric model to simulate the profitability of an alternative replacement policy under pessimistic assumptions about the rate maintenance costs would increase and rental rates would have to be decreased if the company were to keep its rental cars longer than it does under the status quo. Depending on the vehicle type, we find that the company’s expected discounted profits would be between 6% to over 140% higher under the suggested alternative operating strategy where vehicles are kept longer and rental rates of older vehicles are discounted to induce customers to rent them. The company found this analysis to be sufficiently convincing that it undertook an experiment to verify the predictions of the econometric model.     

ECB Monetary Policy Surprises: Identification Through Cojumps in Interest Rates

This paper proposes a new econometric approach to disentangle two distinct response patterns of the yield curve to monetary policy announcements. Based on cojumps in intraday tick data of short‐ and long‐term interest rate futures, we develop a day‐wise test that detects the occurrence of a significant policy surprise and identifies the market perceived source of the surprise. The new test is applied to 133 policy announcements of the European Central Bank (ECB) in the period from 2001 to 2012. Our main findings indicate a good predictability of ECB policy decisions and remarkably stable perceptions about the ECB's policy preferences. Copyright © 2015 John Wiley & Sons, Ltd.     

EVIDENCE ON THE IMPACT OF TARIFF REDUCTIONS ON EMPLOYMENT IN DEVELOPING COUNTRIES: A SYSTEMATIC REVIEW

This paper analyses the evidence on the impact of tariff reductions on employment in developing countries. We carry out a systematic review of the existing empirical literature, and include both, ex post econometric evidence and ex ante Computable General Equilibrium (CGE) simulation studies. The synthesis of results suggests that the effects of tariff reductions on employment are country and trade policy specific. When looking across higher quality econometric studies that control for the endogeneity of tariffs, only a couple of studies have statistically significant results, and these suggest that employment is likely to decrease slightly in the short run following trade liberalization. This is consistent with the notion that there are winners and losers from trade policy reform. These results are in contrast with the CGE findings, which by design incorporate projections of the medium‐run economy‐wide knock‐on effects suggested by economic theory. The synthesis of CGE studies suggests non‐negative effects of trade liberalization on aggregate employment and moderate inter‐sectoral labour reallocation effects.     

Principal components at work: the empirical analysis of monetary policy with large data sets

The empirical analysis of monetary policy requires the construction of instruments for future expected inflation. Dynamic factor models have been applied rather successfully to inflation forecasting. In fact, two competing methods have recently been developed to estimate large‐scale dynamic factor models based, respectively, on static and dynamic principal components. This paper combines the econometric literature on dynamic principal components and the empirical analysis of monetary policy. We assess the two competing methods for extracting factors on the basis of their success in instrumenting future expected inflation in the empirical analysis of monetary policy. We use two large data sets of macroeconomic variables for the USA and for the Euro area. Our results show that estimated factors do provide a useful parsimonious summary of the information used in designing monetary policy. Copyright © 2005 John Wiley & Sons, Ltd.     

Corporate Environmental Reporting and News Coverage of Environmental Issues: an Agenda‐Setting Perspective

Departing from agenda‐setting theory, this paper explores whether environmental content in newspapers is related to corporate environmental agendas presented in corporate environmental reports and annual reports. Based on a sample of 1668 corporate reports published between 1997 and 2008, this paper compares corporate reporting against environmental news content over the same period with time lags of one and two years as well as without time lags. The results suggest that the media agenda and the corporate environmental agenda mirror each other. The results further suggest that, for some issues, there may be an impact of the news media agenda on corporate environmental agendas, but not vice versa. Copyright © 2013 John Wiley & Sons, Ltd and ERP Environment.     

Transmission lags and optimal monetary policy

The credibility problems of monetary policy are enlarged by transmission lags whenever the welfare criterion consists of arguments with differing transmission lags. If, as usually argued, prices react to monetary policy with a longer lag than output, the discretionary bias is substantially increased under a consumer welfare maximizing policy criterion (flexible inflation targeting) in the prototype New Keynesian model. Money growth targeting can significantly reduce the discretionary bias, but is not robust to other specifications of welfare with higher valuation of output stability.     

Exploring external and internal pressures on the environmental behavior of paper enterprises in China: A qualitative study

As one of the typical high‐polluting and high‐energy‐consuming industries in China, the paper industry's environmental behavior has become the focus of a range of stakeholders, policy makers, and the whole society because the industry's business activities are a main source of environmental pollution and contribute to massive energy consumption. This study used a qualitative approach to examine the relative importance of external and internal pressures (EP and IP) in driving the environmental behavior of paper enterprises in China. Based on grounded theory, this study aimed to examine the EP and IP on the environmental behavior of paper enterprises to create a comprehensive theoretical model based on grounded theory code analysis. It was found that government pressure, economic pressure, social pressure, and IP have direct and significant positive effects on the corporate environmental behavior (CEB) of paper enterprises in China. Furthermore, government, economic, and social pressures have indirect and significant positive effects on CEB through other pressures. Finally, the paper concludes with a discussion of these four pressures and provides policy implications.     

EVALUATING MACROECONOMIC FORECASTS: A CONCISE REVIEW OF SOME RECENT DEVELOPMENTS

Macroeconomic forecasts are frequently produced, widely published, intensively discussed, and comprehensively used. The formal evaluation of such forecasts has a long research history. Recently, a new angle to the evaluation of forecasts has been addressed, and in this review we analyze some recent developments from that perspective. The literature on forecast evaluation predominantly assumes that macroeconomic forecasts are generated from econometric models. In practice, however, most macroeconomic forecasts, such as those from the IMF, World Bank, OECD, Federal Reserve Board, Federal Open Market Committee (FOMC), and the ECB, are typically based on econometric model forecasts jointly with human intuition. This seemingly inevitable combination renders most of these forecasts biased and, as such, their evaluation becomes nonstandard. In this review, we consider the evaluation of two forecasts in which: (i) the two forecasts are generated from two distinct econometric models; (ii) one forecast is generated from an econometric model and the other is obtained as a combination of a model and intuition; and (iii) the two forecasts are generated from two distinct (but unknown) combinations of different models and intuition. It is shown that alternative tools are needed to compare and evaluate the forecasts in each of these three situations. These alternative techniques are illustrated by comparing the forecasts from the (econometric) Staff of the Federal Reserve Board and the FOMC on inflation, unemployment, and real GDP growth. It is shown that the FOMC does not forecast significantly better than the Staff, and that the intuition of the FOMC does not add significantly in forecasting the actual values of the economic fundamentals. This would seem to belie the purported expertise of the FOMC.