Data&Code
Data&Code
[3] Panel Regression Kink Model with Unknown Thresholds
This code extends the regression kink model with an unknown developed by Hansen (2017) to a panel kink model with heterogeneous unknown thresholds.
Matsuoka, H. "Hidden Fiscal Unsustainability: Evidence from Real-Time Data in the Euro Area," German Economic Review, forthcoming.
[2] A cross-country database of sectoral labor productivity
The database consists of sectoral labor productivity statistics for 91 countries, and 8 sectors covering the period up to 2018. It is available for download in Excel and Stata.
"Sectoral Decomposition of Convergence in Labor Productivity: A Re-examination from a New Dataset,"(with Alistair Dieppe),
Empirical Economics, vol. 68, pp. 1829–1859, April 2025.
Working paper versions: [BOFIT(The Bank of Finland Institute for Emerging Economies ) DP] [World Bank WP]
[Previous version] Dieppe, A., and H. Matsuoka. 2020. “Sectoral Sources of Productivity Growth” in Global Productivity: Trends, Drivers, and Policies, ed. A. Dieppe. Washington, DC: World Bank. Chapter7 of the book | Data Annex | Excel | Stata
Database consists of sectoral and aggregate labor productivity statistics for 103 countries, and nine sectors covering the period up to 2017. Compared with the earlier literature, it employs a larger and more diverse sample of countries. Database includes five main variables: 1. Nominal value added (current prices, local currency, millions), 2. Real value added (2010 constant prices, local currency, millions), 3. Employment (thousands), 4. Labor productivity (2010 constant prices, local currency, thousands), 5. Labor productivity (2011 international PPP exchange rate, thousands).
This code allows estimating the GPSTR model. Matsuoka (2022) makes a methodological contribution towards the generalized panel smooth transition regression (GPSTR) model by combining two approaches: the Panel smooth transition regression(PSTR) and the general logistic model (GLM).
Matsuoka, H. (2022) "Debt Intolerance: Threshold level and composition,"Oxford Bulletin of Economics and Statistics. vol. 84, pp.894-932.