Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

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.

Business environment --- E-Business --- Economic Theory & Research --- Enterprise surveys --- Equipment --- Imputation method --- Imputation process --- Information and Communication Technologies --- Information and Records Management --- Information Security & Privacy --- Innovation --- Intangible assets --- Macroeconomics and Economic Growth --- Manufacturing --- Marketing --- Missing data --- Missing value --- Missing values --- Multiple imputation --- Multiple imputations --- Private sector --- Private Sector Development --- Productivity --- Result --- Results --- Science and Technology Development --- Statistical & Mathematical Sciences --- Telecommunications --- Web