Empirical Econometric Evaluation of Alternative Methods of Dealing with Missing Values in Investment Climate Surveys

Investment climate Surveys are valuable instruments that improve our understanding of the economic, social, political, and institutional factors determining economic growth, particularly in emerging and transition economies. However, at the same time, they have to overcome some difficult issues related to the quality of the information provided; measurement errors, outlier observations, and missing data that are frequently found in these datasets. This paper discusses the applicability of recent procedures to deal with missing observations in investment climate surveys. In particular, it presents a simple replacement mechanism -- for application in models with a large number of explanatory variables -- which in turn is a proxy of two methods: multiple imputations and an export-import algorithm. The performance of this method in the context of total factor productivity estimation in extended production functions is evaluated using investment climate surveys from four countries: India, South Africa, Tanzania, and Turkey. It is shown that the method is very robust and performs reasonably well even under different assumptions on the nature of the mechanism generating missing data.

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Bibliographic Details
Main Authors: Escribano, Alvaro, Pena, Jorge, Guasch, J. Luis
Format: Policy Research Working Paper biblioteca
Language:English
Published: 2010-06-01
Subjects:ALGORITHMS, BENCHMARK, BIASES, BOOTSTRAP, BUSINESS ENVIRONMENT, CLASSIFICATION, CLASSIFYING, CLUSTERING, COMPETITIVENESS, COMPUTATION, CUSTOMS, DESCRIPTION, DESCRIPTIVE STATISTICS, E-MAIL, ECONOMETRIC ANALYSIS, ECONOMETRIC MODELS, ECONOMIC PERFORMANCE, ELECTRICITY, ENTERPRISE SURVEYS, EQUATIONS, EQUIPMENT, EXOGENOUS VARIABLES, EXPORTS, FOREIGN CURRENCY, IMPUTATION METHOD, IMPUTATION PROCESS, INDEPENDENT VARIABLES, INNOVATION, INSPECTIONS, INTANGIBLE ASSETS, LICENSE, LINEAR REGRESSION, MANUFACTURING, MARKET SHARE, MARKETING, MATRICES, MATRIX, MEASUREMENT ERRORS, MISSING DATA, MISSING OBSERVATIONS, MISSING VALUE, MISSING VALUES, MULTIPLE IMPUTATION, MULTIPLE IMPUTATIONS, NEW TECHNOLOGIES, NEW TECHNOLOGY, NORMAL DISTRIBUTIONS, OUTLIERS, OUTSOURCING, PRIVATE SECTOR, PROBABILITY, PROBABILITY MODELS, PRODUCT INNOVATION, PRODUCTION FUNCTION, PRODUCTION FUNCTIONS, PRODUCTIVITY, PUBLISHING, R&D, RANDOM SAMPLING, REGRESSION ANALYSIS, RESEARCHER, RESEARCHERS, RESULT, RESULTS, SAMPLE SELECTION, SAMPLE SIZE, SENSITIVITY ANALYSIS, STANDARD DEVIATION, STANDARD ERRORS, STATISTICAL ANALYSES, STATISTICAL ANALYSIS, STATISTICAL METHODS, STATISTICIANS, TELECOMMUNICATIONS, TOTAL FACTOR PRODUCTIVITY, TRANSITION ECONOMIES, USES, VALIDITY, WEB, WEB PAGE,
Online Access:http://www-wds.worldbank.org/external/default/main?menuPK=64187510&pagePK=64193027&piPK=64187937&theSitePK=523679&menuPK=64187510&searchMenuPK=64187283&siteName=WDS&entityID=000158349_20100623140811
http://hdl.handle.net/10986/3832
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