Why has economic growth slowed down in Indonesia? An investigation into the Indonesian business cycle using an estimated DSGE model

Dutu, Richard

doi:10.1016/j.asieco.2016.06.003

Cited by 22 publications

(31 citation statements)

References 9 publications

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“…This result is largely consistent with the corresponding estimates in Dutu (2016) using Indonesian data and in Eo and Lie (2018) using US data. Hence, one cannot statistically reject the hypothesis that once inflation target is incorporated into the indexation mechanism, there is no need for the backward-looking inflation to match the persistence of both inflation series (producer-price inflation and import-price inflation).…”

Section: Posterior Estimates Of the Parameterssupporting

confidence: 88%

“…For importers, the Calvo parameter is estimated to be 0.42. On the Taylor-rule parameters, w p is estimated to be 1.65, which is about the same as the estimate in Dutu (2016). On the Taylor-rule parameters, w p is estimated to be 1.65, which is about the same as the estimate in Dutu (2016).…”

Section: Posterior Estimates Of the Parametersmentioning

confidence: 60%

“…That the elasticity (1/r) is above unity accords well with the estimate in Justiniano and Preston (2010) for the Canadian economy. Habit formation is thus not important to match the persistence of output and consumption in Indonesia over the estimated sample period, in contrast to the high estimate of h (around 0.9) in Dutu (2016). Habit formation is thus not important to match the persistence of output and consumption in Indonesia over the estimated sample period, in contrast to the high estimate of h (around 0.9) in Dutu (2016).…”

Section: Posterior Estimates Of the Parametersmentioning

confidence: 82%

“…The openness parameter, a, is set equal to the actual average share of imports as a fraction of GDP from 2005 to 2017 (around 20 per cent). 5 Adolfson et al (2007) and Dutu (2016) also calibrate a very high value of q p (0.975). Following Cogley et al (2010) and Bhattarai et al (2016), the AR(1) persistence parameter of the inflation-target process q p is calibrated to 0.995.…”

Section: Data and Prior Distributionmentioning

confidence: 89%

“…Not surprisingly, there is a growing list of recent studies on calibrating and estimating DSGE models for Indonesia to analyze various issues: among others, , Alamsyah (2004), Tjahjono and Waluyo (2010), Harmanta et al (2013Harmanta et al ( ), (2014, Dutu (2016), and Sahminan et al (2017). Interests on this literature have been ramped up by Bank Indonesia's (and to some extent, the Ministry of Finance's) increasing need for a good-fitting and reliable DSGE model to be used for forecasting and policy simulations.…”

Section: Related Literature and Contributionmentioning

confidence: 99%

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Observed Inflation‐target Adjustments in an Estimated DSGE Model for Indonesia: Do They Matter for Aggregate Fluctuations?

Lie

2019

J of App Econs and Policy

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This paper investigates the role of observed official inflation-target adjustments in aggregate macroeconomic fluctuations in Indonesia, using an estimated Dynamic Stochastic General Equilibrium model. The paper finds that these adjustments or shocks play a non-trivial role in the fluctuations of inflation and nominal interest rate in Indonesia. Output fluctuations, however, are virtually unaffected. A counterfactual exercise shows that a faster disinflation policy, through an immediate decrease in Bank Indonesia's inflation target, may have resulted in a lower average inflation and nominal interest rate, with virtually no output loss. The paper also provides additional insights on the contribution of various shocks in driving aggregate fluctuations in Indonesia. Technology and monetary-policy shocks are found to be the main driving factor for both output and inflation fluctuations. Movements in the nominal interest rate are mostly driven by preference and riskpremium shocks, with inflation-target shocks playing a larger role in the longer run.Keywords: inflation target, inflation-target adjustments or shocks, DSGE model for Indonesia, source of aggregate fluctuations, Bank Indonesia. *Thanks to Yunjong Eo for valuable discussions and suggestions. Comments and suggestions from an anonymous referee are gratefully acknowledged. All errors are mine. The online appendix of the paper can be found at Since 2005, the official targets are set by the government, in close coordination with and with input from Bank Indonesia, through a Minister of Finance's decree. The targets are established for three year periods and are usually announced in advancefor example, the targets for 2013, 2014, and 2015 were set and announced in the second quarter of 2012 through Decree No. 66/PMK.011/2012. Each announced target is a mid-point target, with AE1 per cent tolerance band. Ó 2019 The Economic Society of Australia 2019 INFLATION TARGET ADJUSTMENTS DSGE INDONESIA 2 Copaciu et al. (2015) develop and estimate a large-scale DSGE model for the Romanian economy. In the paper, actual inflation-target data are used as one of the observables. 3An earlier version of this paper considers another extension of the standard model involving a money-holding friction due to a cash-in-advance (CIA) constraint. This additional friction is motivated by the fact that Indonesia is still largely a cash-oriented society (records from BI show that in 2015 almost 90 per cent of all transactions in Indonesia are cash transactions). While the inclusion of this friction improves the marginal likelihood of the model and the estimated CIA parameter is economically and statistically significant, the baseline results and their interpretation are largely the same, with or without this friction.

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Section: Posterior Estimates Of the Parameterssupporting

confidence: 88%

Section: Posterior Estimates Of the Parametersmentioning

confidence: 60%