| |
|
|
|
|
|
|
|
1. |
Record Nr. |
UNINA9910155013403321 |
|
|
Autore |
Benk Szilard |
|
|
Titolo |
Tuning in RBC Growth Spectra / / Szilard Benk, Tamas Csabafi, Jing Dang, Max Gillman, Michal Kejak |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Washington, D.C. : , : International Monetary Fund, , 2016 |
|
|
|
|
|
|
|
ISBN |
|
1-4755-5685-3 |
1-4755-5704-3 |
|
|
|
|
|
|
|
|
Descrizione fisica |
|
1 online resource (52 pages) : illustrations (some color) |
|
|
|
|
|
|
Collana |
|
|
|
|
|
|
Altri autori (Persone) |
|
CsabafiTamas |
DangJing |
GillmanMax |
KejakMichal |
|
|
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Business cycles - United States |
Human capital - United States |
Labor |
Macroeconomics |
Production and Operations Management |
Neoclassical |
Business Fluctuations |
Cycles |
Trade: General |
Human Capital |
Skills |
Occupational Choice |
Labor Productivity |
Production |
Cost |
Capital and Total Factor Productivity |
Capacity |
Labor Economics: General |
Prices, Business Fluctuations, and Cycles: General (includes Measurement and Data) |
Macroeconomics: Production |
Labour |
income economics |
Economic growth |
Human capital |
Total factor productivity |
|
|
|
|
|
|
|
|
|
|
|
|
Business cycles |
Capacity utilization |
Industrial productivity |
Labor economics |
Industrial capacity |
United States |
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di bibliografia |
|
Includes bibliographical references. |
|
|
|
|
|
|
Sommario/riassunto |
|
For US postwar data, the paper explains central consumption, labor, investment and output correlations and volatilities along with output growth persistence by including a human capital investment sector and a variable physical capital utilization rate. Strong internal "amplication" results from an economy-wide productivity shock across goods and human capital investment sectors that has variances 10,000 fold smaller than in the standard RBC TFP shock. Simulated moments are compared to data moments for the business cycle, the low frequency and the Medium Cycle frequency, as well as the high frequency. A metric is provided to gauge that the results have an average of 46% deviation of simulated moments from data moments, for a broad array of targets across all windows. Within this array, key correlations have only a 15% deviation in the business cycle window, and growth persistence only an 8% deviation in the low frequency, which indicates good "propagation". Countercyclic human capital investment time and procyclic physical capital capacity utilization rates are also found as in data. |
|
|
|
|
|
|
|
| |