Gluschenko, Konstantin (2020): Nonlinear Models of Convergence.
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Abstract
A sufficient issue in studies of economic development is whether economies (countries, regions of a country, etc.) converge to one another in terms of per capita income. In this paper, nonlinear asymptotically subsiding trends of income gap in a pair of economies model the convergence process. A few specific forms of such trends are proposed: log-exponential trend, exponential trend, and fractional trend. A pair of economies is deemed converging if time series of their income gap is stationary about any of these trends. To test for stationarity, standard unit root tests are applied with non-standard test statistics that are estimated for each kind of the trends.
Item Type: | MPRA Paper |
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Original Title: | Nonlinear Models of Convergence |
English Title: | Nonlinear Models of Convergence |
Language: | English |
Keywords: | income convergence; time series econometrics; nonlinear time-Series model; unit root |
Subjects: | C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation |
Item ID: | 99316 |
Depositing User: | Konstantin Gluschenko |
Date Deposited: | 30 Mar 2020 11:13 |
Last Modified: | 30 Mar 2020 11:13 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/99316 |