Data-Driven Learning About Trend Productivity Growth
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- Eiji Goto & Jan P.A.M. Jacobs & Simon van Norden, 2025. "Data-Driven Learning About Trend Productivity Growth," CIRANO Working Papers 2025s-29, CIRANO.
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Keywords
; ; ; ;JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- E6 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook
- E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
- O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2025-09-29 (Econometrics)
- NEP-EFF-2025-09-29 (Efficiency and Productivity)
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