Non-market economic valuation in developing countries: Role of participant observation method in CVM analysis

Developing countries have high proportion of black money and related corruption in the society in comparison to the developed ones. This aspect has to be kept in mind while conducting contingent valuation method (CVM) questionnaire survey (in-person) at the site whose economic valuation is being done. Participant observation method (POM) and unstructured interview schedule (UIS) are the two means, which must be used in addition to structured interview schedule during CVM studies in developing countries to arrive at a reasonable non-market economic valuation figure of an environmental amenity. It has been observed that researchers generally ignore this fact during survey for primary data collection among respondents who are quite well off, educated and belong to countries of huge parallel economy. However in the present study, we have utilized these two means during primary data collection for a CVM study and reached the conclusion that CVM has to be used with caution even among educated masses in the developing countries.     

A new multivariate count data model to study multi-category physician prescription behavior

Multivariate count models represent a natural way of accommodating data from multiple product categories when the dependent variable in each category is represented by a positive integer. In this paper, we propose a new simultaneous equation multi-category count data model–the Poisson-lognormal simultaneous equation model–that allows for the Poisson parameter in one equation to be a function of the Poisson parameters in other equations. While generally applicable to any situation where simultaneity is an issue and the dependent variables are measured as counts, such a specification is particularly useful for our empirical application where physicians prescribe drugs in multiple categories. Accounting for the endogeneity of detailing in such situations requires us to explicitly allow for pharmaceutical firms’ detailing activities in one category to be influenced by their activities in other categories. Estimation of such a system of equations using traditional maximum likelihood method is cumbersome, so we propose a simple solution based on using Markov Chain Monte Carlo methods. Our simulation study demonstrates the validity of the solution algorithm and the biases that would result if such simultaneity is ignored in the estimation process.     

Macroeconomic policy and output comovement: The formal and informal sectors in India

Is the informal sector different from the formal sector? We present an aggregative analysis of the formal and informal sectors in India to investigate the extent to which the two can be viewed as broadly homogeneous. Using a macroeconometric framework, the paper analyzes over past three decades the behavior of the two sectors with respect to each other and several government-related policy variables. It is found that the formal and informal sectors display markedly different attributes in terms of their relationship to policy variables. Furthermore, the informal sector appears to be decoupled from the rest of the economy.     

TAX-PRICE REFORM WITH DIRECTLY UNPRODUCTIVE PROFIT-SEEKING (DUP) ACTIVITIES*

This paper explores the extent to which insights available from existing writings on directly unproductive profit-seeking (DUP) activities in international trade modify rules of tax and tariff reform in normative public economics and examines in what way these should affect advice on tax policy usually given to developing countries. The analysis proceeds by developing two models. The first incorporates revenue seeking directly into a standard open economy public finance model and examines whether analysis of policy reform and economic costs of distortionary tariffs must be modified. The second includes a political component in the form of lobbying for subsidies – the expenditure side of the budget – as well as a normative economic component that raises taxes – the revenue side – to finance the social costs of such lobbying. The model can be used to determine the effects of politically determined expenditures on tax setting. The analysis shows that the grammar of welfare-theoretic arguments that underlies the reform and design of tax and tariff structures is robust to the inclusion of DUP activities of the type considered here. In particular, the latter lend no presumption in favor of uniformity in tax and tariff structures. It is argued that existing policy advice on tax and tariff reform derived from models where DUP activities have traditionally played no role continues to be appropriate when account is taken of formal treatments of DUP-type phenomena extant in the current literature.     

Empirical Analysis of a Dynamic Duopoly Model of Competition

Empirically validating and testing the specification of game theoretic models has received limited attention in the marketing literature. The authors provide an econometric framework for estimating the parameters of response functions when the observed data in the market place are the Nash equilibrium outcomes of an underlying dynamic duopoly game specification. Specifically, the estimation procedure accounts for the joint endogeneity of market shares and marketing efforts of market rivals using a system of simultaneous equations that included the market response function and the Nash equilibrium conditions. A formal statistical test is used to detect model misspecification. The empirical analysis is carried out using data from four product markets: pharmaceutical, soft drink, beer, and detergent. Comparisons are provided with conventional estimation of the response function parameters in which the equilibrium conditions are ignored in the estimation. Managerial implications of the empirical results are discussed.     

THRESHOLD AUTOREGRESSIVE MODELING IN FINANCE: THE PRICE DIFFERENCES OF EQUIVALENT ASSETS1

Threshold autoregressive (TAR) models condition the first moment of a time series on lagged information using a step-function-type nonlinear structure. TAR techniques are expected to be relevant in financial time-series modeling in situations where deviations of prices from equilibrium values depend on discrete transaction costs and where market regulators follow intervention rules based on threshold values of control variables. an important finance application is in modeling the difference in prices of equivalent assets in the presence of transaction costs. the focus of this paper is on motivating the use of TAR models in this context and on the statistical estimation and testing procedures. the procedures are illustrated by modeling the difference between the prices of an index futures contract and the equivalent underlying cash index. It is found that the hypothesis of linearity is conclusively rejected in favor of threshold nonlinearity and that the estimated thresholds are largely consistent with arbitrage-related transaction costs.     

Money and production, and liquidity trap

We prove the existence of monetary equilibrium in a finite horizon economy with production. We also show that if agents expect the monetary authority to significantly decrease the supply of bank money available for short-term loans in the future, then the economy will fall into a liquidity trap today.     

A Ricardian Analysis of the Distribution of Climate Change Impacts on Agriculture across Agro-Ecological Zones in Africa

This paper examines the distribution of climate change impacts across the sixteen Agro-Ecological Zones (AEZs) of Africa. We combine net revenue from livestock and crops and regress total net revenue on a set of climate, soil, and socio-economic variables with and without country fixed effects. Although African crop net revenue is very sensitive to climate change, combined livestock and crop net revenue is more climate resilient. With the hot and dry CCC climate scenario, average damage estimates reach 27% by 2100, but with the mild and wet PCM scenario, African farmers will benefit. The analysis of AEZs implies that the effects of climate change will be quite different across Africa. For example, currently productive areas such as dry/moist savannah are more vulnerable to climate change while currently less productive agricultural zones such as humid forest or sub-humid AEZs become more productive in the future. S. Niggol Seo is the Consultant to the World Bank.     

Investigating brand preferences across social groups and consumption contexts

Using a unique dataset on U.S. beer consumption, we investigate brand preferences of consumers across various social group and context related consumption scenarios (??scenarios??). As sufficient data are not available for each scenario, understanding these preferences requires us to share information across scenarios. Our proposed modeling framework has two main building blocks. The first is a standard continuous random coefficients logit model that the framework reduces to in the absence of information on social groups and consumption contexts. The second component captures variations in mean preferences across scenarios in a parsimonious fashion by decomposing the deviations in preferences from a base scenario into a low dimensional brand map in which the brand locations are fixed across scenarios but the importance weights vary by scenario. In addition to heterogeneity in brand preferences that is reflected in the random coefficients, heterogeneity in preferences across scenarios is accounted for by allowing the brand map itself to have a discrete heterogeneity distribution across consumers. Finally, heterogeneity in preferences within a scenario is accounted for by allowing the importance weights to vary across consumers. Together, these factors allow us to parsimoniously account for preference heterogeneity across brands, consumers and scenarios. We conduct a simulation study to reassure ourselves that using the kind of data that is available to us, our proposed estimator can recover the true model parameters from those data. We find that brand preferences vary considerably across the different social groups and consumption contexts as well as across different consumer segments. Despite the sparse data on specific brand-scenario combinations, our approach facilitates such an analysis and assessment of the relative strengths of brands in each of these scenarios. This could provide useful guidance to the brand managers of the smaller brands whose overall preference level might be low but which enjoy a customer franchise in a particular segment or in a particular context or a social group setting.