Choose an application

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

Export and import price indices are essential for assessing the impact of international trade on the domestic economy. Among their most important uses are analyzing developments in the trade balance, measuring foreign prices' contribution to domestic inflation, and deflating nominal values of exports and imports for estimating the volume of gross domestic product. This paper discusses the main uses of trade indices and the data sources used to compile them. It also presents various approaches used to compile foreign trade price indices, addresses various problems encountered in developing these indices, and provides some recommendations on how to address them.

Exports and Imports --- Macroeconomics --- Methodology for Collecting, Estimating, and Organizing Microeconomic Data --- Methodology for Collecting, Estimating, and Organizing Macroeconomic Data --- Data Access --- Trade: General --- Price Level --- Inflation --- Deflation --- International economics --- Price indexes --- Import price indexes --- Export price indexes --- Imports --- Exports --- Prices --- International trade --- Finland

Choose an application

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

Index number theory informs us that if data on matched prices and quantities are available, a superlative index number formula is best to aggregate heterogeneous items, and a unit value index to aggregate homogeneous ones. The formulas can give very different results. Neglected is the practical case of broadly comparable items. This paper provides a formal analysis as to why such formulas differ and proposes a solution to this index number problem.

Business & Economics --- Economic Theory --- Index numbers (Economics) --- Economic indicators. --- Business indicators --- Economic indicators --- Indicators, Business --- Indicators, Economic --- Leading indicators --- Numbers, Index --- Economic history --- Quality of life --- Economic forecasting --- Social indicators --- Economics --- Prices --- Indexation (Economics) --- Macroeconomics --- Index Numbers and Aggregation --- leading indicators --- Methodology for Collecting, Estimating, and Organizing Microeconomic Data --- Price Level --- Inflation --- Deflation --- Production, Pricing, and Market Structure --- Size Distribution of Firms --- Information and Product Quality --- Standardization and Compatibility --- Price indexes --- Export price indexes

Choose an application

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

Consumer price indexes (CPIs) are compiled at the higher (weighted) level using Laspeyres-type arithmetic averages. This paper questions the suitability of such formulas and considers two counterpart alternatives that use geometric averaging, the Geometric Young and the (price-updated) Geometric Lowe. The paper provides a formal decomposition and understanding of the differences between the two. Empirical results are provided using United States CPI data. The findings lead to an advocacy of variants of a hybrid formula suggested by Lent and Dorfman (2009) that substantially reduces bias from Laspeyres-type indexes.

Consumer price indexes --- Consumer price index --- Cost of living indexes --- CPIs (Consumer price indexes) --- Retail price indexes --- Cost and standard of living --- Price indexes --- Econometric models. --- Inflation --- Macroeconomics --- Public Finance --- Index Numbers and Aggregation --- leading indicators --- Methodology for Collecting, Estimating, and Organizing Microeconomic Data --- Price Level --- Deflation --- Labor Economics: General --- National Government Expenditures and Related Policies: General --- Labour --- income economics --- Public finance & taxation --- Labor --- Expenditure --- Prices --- Labor economics --- Expenditures, Public --- United States --- Income economics --- Leading indicators

Choose an application

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

Using micro-data from household expenditure surveys, we document the evolution of consumption poverty in the United States over the last four decades. Employing a price index that appears appropriate for low income households, we show that poverty has not declined materially since the 1980s and even increased for the young. We then analyze which social and economic factors help explain the extent of poverty in the U.S. using probit, tobit, and machine learning techniques. Our results are threefold. First, we identify the poor as more likely to be minorities, without a college education, never married, and living in the Midwest. Second, the importance of some factors, such as race and ethnicity, for determining poverty has declined over the last decades but they remain significant. Third, we find that social and economic factors can only partially capture the likelihood of being poor, pointing to the possibility that random factors (“bad luck”) could play a significant role.

United States --- Macroeconomics --- Economics: General --- Poverty and Homelessness --- Intelligence (AI) & Semantics --- Methodology for Collecting, Estimating, and Organizing Microeconomic Data --- Measurement and Analysis of Poverty --- Government Policy --- Provision and Effects of Welfare Program --- Welfare, Well-Being, and Poverty: General --- Macroeconomics: Consumption --- Saving --- Wealth --- Aggregate Factor Income Distribution --- Technological Change: Choices and Consequences --- Diffusion Processes --- Economic & financial crises & disasters --- Economics of specific sectors --- Poverty & precarity --- Machine learning --- Poverty --- Consumption --- National accounts --- Poverty measurement --- Income --- Technology --- Currency crises --- Informal sector --- Economics

Choose an application

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

This paper incorporates time-to-build into the standard investment model with convex adjustment costs. The empirical Euler equation is estimated using a U.S. firm-level panel from Compustat. In spite of the introduction of time-to-build, the magnitude of the implied adjustment costs is unrealistically high. Exploiting another approach, I test directly the restrictions imposed by time-to-build on the investment equation. The results indicate that these restrictions cannot be rejected for five of the sixteen industries in the sample. Finally I show that time-to-build can explain approximately one-third of the variation in persistence of structure investment across four-digit industries.

Econometrics --- Infrastructure --- Investments: Bonds --- Investments: Stocks --- Industries: Manufacturing --- Methodology for Collecting, Estimating, and Organizing Microeconomic Data --- Production --- Cost --- Capital and Total Factor Productivity --- Capacity --- Investment --- Capital --- Intangible Capital --- Estimation --- Pension Funds --- Non-bank Financial Institutions --- Financial Instruments --- Institutional Investors --- Industry Studies: Manufacturing: General --- Industry Studies: Transportation and Utilities: General --- General Financial Markets: General (includes Measurement and Data) --- Investment & securities --- Econometrics & economic statistics --- Manufacturing industries --- Macroeconomics --- Estimation techniques --- Stocks --- Manufacturing --- Transportation --- Bonds --- Financial institutions --- Econometric analysis --- Economic sectors --- National accounts --- Econometric models --- Saving and investment --- United Kingdom