Advanced Econometrics Research Articles

Assessing the market power of millers and wholesalers in the Bangladesh rice sector

PurposeBecause of the increasing differential between farm and retail prices, the study proposes to investigate the extent of market power in the rice value chain of Bangladesh using advanced econometric techniques.Design/methodology/approachUsing a Stochastic Frontier Estimation approach on cross-sectional data, the study examines the price spread along the rice value chain to determine whether millers and wholesalers exercise market power.FindingsEmpirical results reveal that, on average, rice millers and wholesalers charge 33 and 29% above the marginal cost, respectively. This study confirms the non-competitive behavior of the rice market with wholesalers and millers wielding substantial market powerResearch limitations/implicationsA limitation of the study is that it does not include the retailers who also play a major role in the Bangladesh rice value chain. This is left for future study.Originality/valueThis study combines primary and secondary data collected on the Bangladesh rice sector to examine the market power of two major players along the value chain, millers and wholesalers, using an advanced econometrics approach.

Exchange Rate Risk in the U.S. Stock Market: A Pooled Panel Data Regression Approach

This paper focuses on revisiting an old issue by advanced econometrics analysis: the risks in the U.S. stock market. We analyze the firm's exposure to exchange rate, interest rate, and market shocks by the pooled regression with the error cross-section dependency. We not only examine the exchange market, and interest rate exposure to U.S. firm values in 396 samples, but we also investigate those patterns to the firms within each of the 10 specific industries by which way we may detect the direction of capital flows before and after two well-known financial crises that occurred in 2001 and 2008. All empirical results show the significant industry-specific sensitivity to these three risks which are in marked contrast to the findings that have been assessed thus far in current literature. Our results indicate: (i) in which industry the capital flows go (industry-specific effect) before and after crises; (ii) which currency, market index, and interest rate play a more important role in the sensitivity to U.S. firm stock returns before and after crises; and (iii) the prospect on hedging portfolio setting for investors before and after crises, which is consistent with the finding of Campbell {it et al.} (2010) and Lusting {it et al.} (2011).

The Impact of Foreign Agricultural Aid and Total Foreign Aid on Agricultural Output in African Countries: New Evidence from Panel Data Analysis

AbstractOfficial Development Assistance may play an important role in increasing the resources to finance the agriculture sector and improve agricultural outcomes in African countries. Although this is a relevant issue, very few studies have investigated the link between foreign agricultural aid and national agricultural output. Using advanced econometrics techniques, this paper examines the impact of foreign agricultural aid and foreign aid on agriculture output in the panel data set of 29 African countries over the period of 1975–2013. In particular, we employed two estimation methods: Augmented Mean Group and Common Correlated Effects‐2SLS. The first method accounts for heterogeneous slope coefficients across group members and cross‐sectional dependency among variables, whereas the second method accounts for endogenous regressors. Our main findings indicate a small and positive impact of foreign agricultural aid and total foreign aid on agricultural output for low‐ and middle‐income countries. Furthermore, the Pairwise Dumitrescu‐Hurlin Panel Causality test shows evidence of a bidirectional causal relationship between agricultural aid and agricultural output for the full sample, noting that the result changes at the different group income level. Based on the empirical results, recommendations for future policy are given.

An Analysis of Price Behavior of Major Poultry Products in Sri Lanka

Taking its overall importance to the economy, as a whole, including food and nutrition security and better performance of the food supply chain from producer to the consumer, the successive governments tend to take a variety of initiatives to upkeep the sustainability of agri-food supply system, but the scarcity of valid and reliable information on the behavior of prices makes it challenging for policymakers to have timely economic decisions. This study attempts to examine the behavior of prices of major poultry products, including chicken (broiler and curry) and eggs (brown and white) on the justification that which have become regular food items in Sri Lankan menus overtime and the total chicken and egg production in Sri Lanka has increased markedly by about 45.3 and 64.5 percent, respectively, during the period of 2003 to 2012. The time-series data were taken up with advanced econometrics models on price analysis, including the ARIMA and SARIMA models which provide efficient forecasts of weekly real prices of different poultry products. It founds that the increasing trend apparent in nominal prices was due to rising inflation of the economy, and the real prices of these products stagnated overtime.

Combining machine-based and econometrics methods for policy analytics insights

Computational social science supports study of e-commerce policy analytics issues.Advances have been made for the discovery of new policy-related insights.Areas covered are: business, consumer and social public and private settings.Machine-based methods are combined with explanatory econometrics and statistics.Empirical illustrations are in four contemporary e-commerce research issue areas.Mobile phone stock trading, music popularity, TV viewing, video-on-demand services. Computational Social Science (CSS) has become a mainstream approach in the empirical study of policy analytics issues in various domains of e-commerce research. This article is intended to represent recent advances that have been made for the discovery of new policy-related insights in business, consumer and social settings. The approach discussed is fusion analytics, which combines machine-based methods from Computer Science (CS) and explanatory empiricism involving advanced Econometrics and Statistics. It explores several efforts to conduct research inquiry in different functional areas of Electronic Commerce and Information Systems (IS), with applications that represent different functional areas of business, as well as individual consumer, social and public issues. Recent developments and shifts in the scientific study of technology-related phenomena and Social Science issues in the presence of historically-large datasets prompt new forms of research inquiry. They include blended approaches to research methodology, and more interest in the production of research results that have direct application to industry contexts. This article showcases the methods shifts and several contemporary applications. They discuss: (1) feedback effects in mobile phone-based stock trading; (2) sustainability of top-rank chart popularity of music tracks; (3) household TV viewing patterns; and (4) household sampling and purchases of video-on-demand (VoD) services. The range of applicability of the ideas goes beyond the scope of these illustrations, to include issues in public services, healthcare, product and service deployment, public opinion and elections, electronic auctions, and travel and tourism services. In fact, the coverage is as broad as for-profit and for-non-profit, private and public, and governmental and non-governmental institutions.

Public transit, active travel, and the journey to school: a cross-nested logit analysis

ABSTRACTLike walking and biking, public transit presents an opportunity to accomplish a portion of the recommended daily physical activity. Much of the previous research has been limited to descriptive analyses quantifying the active component of public transit using advanced econometrics models. This paper overcomes this challenge by applying a two-level cross-nested logit model. We use the school trip information of 3441 middle and high school students in Tehran. We show a 1% increase in home-to-school distance reduces physical activity by 0.91%. Considering public transit a solely non-active mode, this reduction equals 2.21%. Therefore, ignoring the ‘quasi-active’ role of public transit overestimates the physical activity reduction of students by 142%. We also indicate a 1% decrease in access to transit stations diminishes physical activity by 0.04%. This diminution is 0.02% when we apply the nested logit model. This is the direct consequence of ignoring the active component of public transit trips.

Public Spending in Selected Caribbean Countries

This study examines the relationship between the ratio of government expenditure to gross domestic product and economic activity by investigating the empirical validity of Wagner’s law in selected Caribbean countries. Additionally, the study tests the ratchet hypothesis by searching for evidence of asymmetry in public spending over the business cycle. It narrows a gap in the Caribbean literature by (1) explicitly considering population structure in the empirical investigation of Wagner’s Law and (2) utilizing advanced econometrics techniques that incorporate nonlinearity in testing causality. The study finds no empirical support for Wagner’s Law, with and without population structure taken into account. However, the ratchet hypothesis is validated. The findings provide useful information for policy makers that can help broaden their understanding of the relationship between government spending and national income, which could aid policy formulation.

Three Pitches for Three Papers that EMR Would Like to Publish

Three Pitches for Three Papers that <i><scp>EMR</scp></i> Would Like to Publish

Advanced Econometric Theory by John S. Chipman

Advanced Econometric Theory by John S. Chipman

Are Indian consumers brand conscious? Insights for global retailers

PurposeThe purpose of this paper is to assess Indian consumers' brand consciousness by examining their brand knowledge, purchase behaviour and perceptions of foreign brands. It provides key inputs for global retailers to harness the potential in growing consumerism in India.Design/methodology/approachA survey of 300 Indian consumers was conducted and the data were analysed using descriptive and simple regression techniques.FindingsThe study found that brand purchase in India varies across product categories. At present, consumer knowledge and use of foreign brands is low, and Indian consumers are price‐sensitive. Indian consumers are experimenting with brands and would like more foreign brands to enter the Indian market.Research limitations/implicationsDue to the small sample size, advanced econometrics techniques could not be used to analyse the dataset.Originality/valueThe paper is the first to assess the impact of retail liberalisation on Indian consumers' shopping behaviour, particularly their brand consciousness.

Cointegration and causal relationships among steel prices of Mainland China, Taiwan, and USA in the presence of multiple structural changes

Variation in the price of steel is an important factor to take into consideration when discussing cost control and management decisions in the construction industry. We employ various conventional and advanced econometrics methods to examine the interrelationships of steel prices in three related markets during the time period June 2002 to May 2010: Mainland China (CH), Taiwan (TW), and the United States (US). We adopt the Gregory and Hansen (GH) test and regime-switching (RS) model for cointegration, both of which accommodate endogenous structural break(s), to produce a more accurate analysis of a period in the presence of structural change(s). The empirical result of the RS cointegration test with respect to multiple structural breaks suggests a long-run equilibrium relationship among the three variables considered. This finding differs from the result of the GH test but confirms the result of the conventional Johansen test. Furthermore, the results of the Granger causality test indicate that both CH and US steel prices have great influence on the TW steel price; the Taiwanese steel market is closely linked with China and US steel markets in the long run.

A History of Japanese Developments in Econometrics

In Japan the systematic collection of economic data, including the prices of such commodities as rice, started for policy purposes in the sixteenth century. Yet such external impacts as the Tokyo meeting of the International Statistical Institute (1930) and the visit of two founding members of the Econometric Society (established 1930) to Japan were instrumental in promoting statistical studies and inspiring Japanese students to study abroad. Eiichi Sugimoto was trained in Berlin and drew a shifting demand curve for rice over time in a three-dimensional space in 1935. After World War II, Shinichi Ichimura, Michio Hatanaka, and Takeshi Amemiya were trained in the United States and introduced to empirical studies. Ichimura became responsible for building macroeconometric models and input-output tables for the Japanese and other East Asian economies. Hatanaka and Amemiya contributed to a more advanced econometrics thanks to the abundant use of U.S. economic data.

Marketing Mix Modeling for the Tourism Industry: A Best Practices Approach

AbstractThe intent of this paper is to introduce marketing managers and tourism researchers to an analytic tool used to optimize the allocation of a firm’s marketing budget in such a way that provides the greatest likelihood of producing the strongest return-on-investment. Marketing mix modeling combines advanced econometrics with marketing science to objectively measure the relative productivity of a complete set of marketing programs or initiatives to produce transient tourism sales. Discussed and demonstrated in this paper are the steps in performing such an analysis, how to avoid its major pitfalls, and the benefits that can be derived from the analysis. Extensions of the marketing mix method to include the effects of the social media and product driven strategies are briefly discussed.

Jobs, Jobs, Jobs: Communications Policy and Employment Effects in the Information Sector

The Federal Communications Commission has recently proposed a wide assortment of regulations for both wireline and wireless providers that may affect the investment decisions of firms. A number of recent studies conclude that employment, both in and outside the communications industry, is highly responsive to capital expenditures by communications firms. Consequently, it is argued that, depending on the response of firms to regulatory interventions, public policy may have significant positive – or negative – employment effects. In this BULLETIN, we present a new approach to measuring employment effects by estimating an “employment multiplier” using advanced time-series econometrics. Statistical testing indicates a causal relationship between capital expenditures and jobs in the Information sector. A 10% negative shock to expenditures in the Information sector results in an average loss of about 130,000 information-sector jobs per year in the ensuing five years. Including indirect jobs, these job losses could be as high as 327,600 jobs. Our econometrically estimated employment effects are 40% greater than many earlier studies on this topic. The estimated employment multiplier is 10 Information sector jobs for each million in expenditure, and perhaps 24 jobs per-million across the entire economy. Lost earnings over a five-year period are estimated to be $100 billion. Moreover, we demonstrate that communications jobs are not typical jobs – these jobs (i) have median earnings 45% higher than the typical private-sector job; (ii) have proven relatively resilient to recessionary forces; and (iii) have a union membership rate over twice the national average, a statistic some policymakers will consider significant when evaluating regulatory policies that threaten investment incentives.

Modelling the time‐varying volatility of equities returns in Kenya

PurposeThe paper seeks to investigate the relationship between stock volatility and returns in the Nairobi Stock Exchange, Kenya. It uses daily returns data over the period January 2006 to April 2009.Design/methodology/approachEmpirical analysis is based on quantitative analysis with emphasis on descriptive statistics, and advanced econometrics models which are well suited to capture the time‐varying volatility. The models utilised in this study fall into the family of generalised autoregressive conditional heteroscedasticity models.FindingsThe main findings of the paper are as follows: the equities returns are symmetric but leptokurtic and thus not normally distributed; volatility of returns is highly persistent; the leverage effects are not significant; and the impact of news on volatility is not significantly asymmetric.Practical implicationsThe findings of this paper will aid policy makers, policy analysts, investors, and academics to gain in‐depth understanding of dynamics of the equities returns in Kenya particularly, with regard to leverage and impact of news.Originality/valueThe paper was conducted at a time when the volatility of the equity market returns in the global stock markets in general and Kenya in particular was high on account of the global financial crisis and the aftermath of the post‐election violence in Kenya. Given that excess volatility in the stock market undermines the reliability of stock market prices as a signal to the true value of the firm, the findings of this paper will provide useful insights in the assessment of portfolio allocation and investment decisions in Kenya.

THE ET INTERVIEW: TAKESHI AMEMIYA: Interviewed by James L. Powell

Much of the credit for the outpouring of research on nonlinear models in the 1970s—particularly limited dependent variable models—should go to Takeshi Amemiya. His classic 1973 Econometrica article on estimation of the parameters of the Tobit model [11] set a new standard for mathematical rigor in theoretical econometrics. During his career, which spans nearly four decades, Takeshi's research contributions to econometrics have touched on most of the central models for empirical economics, including linear and nonlinear simultaneous equations models, distributed lag models, heteroskedastic and random coefficient models, qualitative response models, censored and truncated regression and selection models, transformed regression models, choice-based sampling models, and duration models. His 1985 text, Advanced Econometrics [44], became the standard reference for second-year graduate microeconometrics courses at the leading graduate programs in economics.Takeshi's research accomplishments have been accompanied by numerous professional honors. He is a Fellow of the Econometric Society, the American Statistical Association, and the American Academy of Arts and Sciences and was awarded Guggenheim and Humboldt Fellowships. Takeshi also has a distinguished record of professional service; he served briefly as a co-editor of Econometrica and has been a co-editor of the Journal of Econometrics since 1982.This interview was conducted in Takeshi Amemiya's office at Stanford University in March 2004. In recent years his interests have turned to comparative study of Greek and Japanese culture and mythology—his scholarship includes a Japanese translation of an English research monograph on Aristotle's Ethics [58]—and the discussion starts with this topic before turning to his unusual education, career as an econometric theorist, and variety of outside interests. His remarks reveal both his careful attention to detail and the dry humor that his colleagues and former students (like me) savor.

Generalized Method of Moments and Empirical Likelihood

Generalized method of moments (GMM) estimation has become an important unifying framework for inference in econometrics in the last 20 years. It can be thought of as encompassing almost all of the common estimation methods, such as maximum likelihood, ordinary least squares, instrumental variables, and two-stage least squares, and nowadays is an important part of all advanced econometrics textbooks. The GMM approach links nicely to economic theory where orthogonality conditions that can serve as such moment functions often arise from optimizing behavior of agents. Much work has been done on these methods since the seminal article by Hansen, and much remains in progress. This article discusses some of the developments since Hansen's original work. In particular, it focuses on some of the recent work on empirical likelihood–type estimators, which circumvent the need for a first step in which the optimal weight matrix is estimated and have attractive information theoretic interpretations.

TOPICS IN ADVANCED ECONOMETRICS: ESTIMATION, TESTING, AND SPECIFICATION OF CROSS-SECTION AND TIME SERIES MODELS

This book, Topics in Advanced Econometrics, is written primarily as a textbook for an advanced graduate econometrics course. The topics covered include consistent model specification testing, unit roots and cointegration, and nonparametric regression estimation; they are mainly the topics in which Professor Bierens has made significant contributions to the literature over the last 15 years. This book is unusual as a textbook in the sense that it treats both cross-sectional and time series (i.e., both subscript i and t) issues in econometrics at an advanced level. Most of the results given, other than those available in standard econometrics or statistics textbooks, are drawn from the published work of the author. The book is very useful because it puts together a number of important current issues that have been treated separately in the literature and presents them systematically using a well-organized set of statistical tools. Another advantage of this book is that the materials given are almost self-contained, making this book suitable for self-tuition. This book thus ideally suits students who need tools for independent research especially in the area of nonlinear and nonparametric models and time series analysis. It will also be useful to more advanced researchers who are interested in a thorough understanding of some of the author's original and influential work in these areas.

Topics in Advanced Econometrics.

In this book Herman Bierens provides a mathematically rigorous treatment of a number of timely topics in advanced econometrics. His subjects include nonlinear estimation, maximum likelihood theory, ARMA and ARMAX models, unit roots and cointegration, and nonparametric regression, together with an extensive and thorough treatment of the necessary probability theory. Professor Bierens' study is uniquely self-contained, providing the reader with a selection of the latest developments in econometric theory, along with the required introductory material on each topic. It will be of great use to graduate students of econometrics and statistics, and is particularly suitable for self-tuition.

Topics in Advanced Econometrics.

5. Topics in Advanced Econometrics. By H. J. Bierens. ISBN 0 521 41900 X. Cambridge University Press, Cambridge, 1994. 256 pp. £30.