UNDERSTANDING INDONESIA’S MACROECONOMIC DATA: WHAT DO WE KNOW AND WHAT ARE THE IMPLICATIONS?
Keywords:
Unit root; Macroeconomic data; Structural breaks; Shocks; Econometric Modelling
Abstract
Unit root properties of macroeconomic data are important for both econometric modelling specifications and policy making. The form of variables (whether they are a unit root process) helps determine the correct econometric modelling. Equally, the form of variables helps explain how they react to shocks (both internal and external). Macroeconomic time-series data are often at the forefront of shock analysis and econometric modelling. There is a growing emphasis on research on Indonesia using time-series data; yet, there is limited understanding of data characteristics and shock response of these data. Using an extensive dataset comprising 33 macroeconomic time-series variables, we provide an informative empirical analysis of unit root properties of data. We find that regardless of data frequencies the empirical evidence of unit roots is mixed, some series respond quickly to shocks others do take time, and almost every macroeconomic data suffers from structural breaks. We draw implications of these findings.
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References
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Narayan, P.K. (2006a). Are bilateral exchange rates stationary? Evidence from Lagrange multiplier unit root tests for India. Applied Economics, 38, 63-70.
Narayan, P.K. (2006b). Examining structural breaks and growth rates in international health expenditures. Journal of Health Economics, 25, 877-890.
Narayan, P. (2008). Revisiting the US money demand function: an application of the Lagrange multiplier structural break unit root test and the bounds test for a long run relationship. Applied Economics, 40, 897-904.
Nelson, C., and Plosser, C. (1982). Trends and random walks in macroeconomic time series: some evidence and implications. Journal of Monetary Economics, 10, 139-169.
Niang, A., Diagne, A., and Pichery, M. (2011). Exploring the finance-real economy link in U.S.: Empirical evidence from panel unit root and cointegration analysis. Empirical Economics, 40, 253-268.
Perron, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica, 57, 1361-1401.
Smyth, R. (2003). Unemployment Hysteresis in Australian States and Territories: Evidence from Panel Data Unit Root Tests. The Australian Economic Review, 36, 181-192.
Sowmya, S., and Prasanna, K. (2018). Yield curve interactions with the macroeconomic factors during global financial crisis among Asian markets. International Review of Economic and Finance 54, 178-192.
Tanuwidjaja, E., and Choy, K.M. (2006). Central bank credibility and monetary policy in Indonesia. Journal of Policy Modeling 28, 1011-1022.
Aslanidis, N., and Fountas, S. (2014). Is real GDP stationary? Evidence from a panel unit root test with cross-sectional dependence and historical data. Empirical Economics, 46, 101-108.
Cavaliere, G., and Xu, F. (2014). Testing for unit roots in bounded time series. Journal of Econometrics, 178, 259-272.
Chambers, M. (2015). Testing for a unit root in a near integrated model with skip-sampled data. Journal of Time Series Analysis, 36, 630-649.
Chang, T., Chang, H-L., Chu, H-P., and Su, C-W. (2006). Does PPP hold in African countries? Further evidence based on a highly dynamic non-linear (logistic) unit root test. Applied Economics, 38, 2453-2459.
Chang, T., Yang, M., Liao, H-C., and Lee, C-H. (2007). Hysteresis in unemployment: empirical evidence from Taiwan's region data based on panel unit root tests. Applied Economics, 39(10), 1335-1340.
Charles, A., and Darné, O. (2012). Trends and random walks in macroeconomic time series: A reappraisal. Journal of Macroeconomics, 34, 167-180.
Choi, I. (2001). Unit root tests for panel data. Journal of International Money and Finance, 20, 249-272.
Chowdhury, A., Uddin, M., and Anderson, K., (2018). Liquidity and macroeconomic management in emerging markets. Emerging Markets Review 34, 1-24.
Djuranovil, L., (2014). The Indonesian macroeconomy and the yield curve: A dynamic latent factor approach. Journal of Asian Economics, 34, 1-15.
Drakos, A., Kouretas, G., and Vlamis, P. (2018). Saving, investment and capital mobility in EU member countries: A panel data analysis of the Feldstein–Horioka puzzle. Applied Economics, 50, 3798-3811.
Dutu, R., (2016). Why has economic growth slowed down in Indonesia? An investigation into the Indonesian business cycle using an estimated DSGE model. Journal of Asian Economics 45, 46-55.
Gil-Alana, L., and Robinson, P. (1997). Testing the unit root and other non-stationarity hypothesis in macroeconomic time series. Journal of Econometrics, 80, 241-268.
Hadiwibowo, Y., and Komatsu, M., (2011). Trilemma and macroeconomic policies under different financial structures in Indonesia. Journal of Asian Economics 22, 302-310.
Hsing, Y., (2012). Impacts of macroeconomic forces and external shocks on real output for Indonesia. Economic Analysis and Policy 42, 97-104.
Hurlin, C. (2010). What would Nelson and Plosser find had they used panel unit root tests?. Applied Economics, 42, 1515-1531.
Kappler, M. (2009). Do hours worked contain a unit root? Evidence from panel data. Empirical Economics, 36, 531-555.
Lee, J., and Strazicich, M. (2003). Minimum lagrange multiplier unit root test with two structural breaks. Review of Economics and Statistics, 85, 1082-1089.
Li, H., and Park, S. (2018). Testing for a unit root in a nonlinear quantile autoregression framework. Econometric Reviews, 37, 867-892.
Lucas, A. (1995). An outlier robust unit root test with an application to the extended Nelson-Plosser data. Journal of Econometrics, 66, 153-173.
Lumsdaine, R., and Papell, D. (1997). Multiple trend breaks and the unit root hypothesis. Review of Economics and Statistics, 79, 212-218.
Maslyuk, S., and Smyth, R. (2008). Unit root properties of crude oil spot and futures prices. Energy Policy, 36, 2591-2600.
Narayan, P.K., and Liu, R. (2015). A unit root model for trending time-series energy variables. Energy Economics, 50, 391-402.
Narayan, P.K., Liu, R., and Westerlund, J., (2016) A GARCH model for testing market efficiency. Journal of International Financial Markets Institutions and Money, 41, 121-138.
Narayan, P., and Narayan, S. (2010). Is there a unit root in the inflation rate? New evidence from panel data models with multiple structural breaks. Applied Economics, 42, 1661-1670.
Narayan, P., and Popp, S., (2010) A new unit root test with two structural breaks in level and slope at unknown time. Journal of Applied Statistics, 37, 1425-1438.
Narayan, P., and Smyth, R. (2005). Structural breaks and unit roots in Australian macroeconomic time series. Pacific Economic Review, 10, 421-437.
Narayan, P.K., and Smyth, R. (2007). Mean reversion versus random walk in G7 stock prices: evidence from multiple trend break unit root tests. Journal of International Financial Markets Institutions and Money, 17, 152-166.
Narayan, P.K., Narayan, S., and Smyth, R. (2008). Are oil shocks permanent or temporary? Panel evidence from crude oil and NGL production in 60 countries. Energy Economics, 30, 919-936.
Narayan, P.K. (2005a). Did Rabuka’s military coups have a permanent effect or a transitory effect on tourist expenditure in Fiji: Evidence from Vogelsang’s structural break test. Tourism Management, 26, 509-515.
Narayan, P.K. (2005b). The structure of tourist expenditure in Fiji: evidence from unit root structural break tests. Applied Economics, 37, 1157-1161.
Narayan, P.K. (2006a). Are bilateral exchange rates stationary? Evidence from Lagrange multiplier unit root tests for India. Applied Economics, 38, 63-70.
Narayan, P.K. (2006b). Examining structural breaks and growth rates in international health expenditures. Journal of Health Economics, 25, 877-890.
Narayan, P. (2008). Revisiting the US money demand function: an application of the Lagrange multiplier structural break unit root test and the bounds test for a long run relationship. Applied Economics, 40, 897-904.
Nelson, C., and Plosser, C. (1982). Trends and random walks in macroeconomic time series: some evidence and implications. Journal of Monetary Economics, 10, 139-169.
Niang, A., Diagne, A., and Pichery, M. (2011). Exploring the finance-real economy link in U.S.: Empirical evidence from panel unit root and cointegration analysis. Empirical Economics, 40, 253-268.
Perron, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica, 57, 1361-1401.
Smyth, R. (2003). Unemployment Hysteresis in Australian States and Territories: Evidence from Panel Data Unit Root Tests. The Australian Economic Review, 36, 181-192.
Sowmya, S., and Prasanna, K. (2018). Yield curve interactions with the macroeconomic factors during global financial crisis among Asian markets. International Review of Economic and Finance 54, 178-192.
Tanuwidjaja, E., and Choy, K.M. (2006). Central bank credibility and monetary policy in Indonesia. Journal of Policy Modeling 28, 1011-1022.
Published
2018-10-31
How to Cite
Sharma, S., Tobing, L., & Azwar, P. (2018). UNDERSTANDING INDONESIA’S MACROECONOMIC DATA: WHAT DO WE KNOW AND WHAT ARE THE IMPLICATIONS?. Buletin Ekonomi Moneter Dan Perbankan, 21(2), 217-250. https://doi.org/10.21098/bemp.v21i2.967
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Copyright (c) 2018 Susan Sunila Sharma
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Buletin Ekonomi Moneter dan Perbankan / Bulletin of Monetary Economics and Banking is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
