A Dynamic Stochastic General Equilibrium (Dsge) Model to Assess the Impact of Structural Reforms on the Indonesian Economy

Sahminan, Sahminan; Utama, Ginanjar; Rakman, Robbi Nur; Idham, Idham

doi:10.21098/bemp.v20i2.810

Cited by 8 publications

(6 citation statements)

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“…Therefore, the impact of local government intervention in the land market on resource allocation is not only reflected in the allocation of land resources but also its impact on the allocation of capital and labor factors cannot be ignored. Undoubtedly, existing studies suggested that there are other determinants that can also play a decisive role in the growth of TFP such as foreign investment (Mankiw et al, 1992;Umar, 2017), the input in funds for scientific and technological endeavors (Zhou et al, 2019), and government intervention (Sahminan et al, 2017). The policy of LTM is still one of the important factors shaping the green TFP through multiple channels, especially its impacts on the status of resource allocation.…”

Section: Background and Conceptual Frameworkmentioning

confidence: 99%

Assessing the effects of land transfer marketization on green total factor productivity from the perspective of resource allocation: Evidence from China

Jin¹,

Lu²,

Gong³

2022

Front. Environ. Sci.

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Exploring the determinants of green total factor productivity (green TFP) is of great importance to economic performance and ecological sustainability. Based on the data of 30 provincial units in China from 2004 to 2016, this study first analyzes the mechanism of land transfer marketization (LTM) affecting green TFP through resource allocation, then the regional resource allocation level is measured using the indicator of factor market distortion, and regional green TFP is estimated by the slack-based measure (SBM) directional distance function and Malmquist–Luenberger (ML) index. On the basis of that, a panel threshold regression model is used to empirically examine the theoretical mechanism of LTM affecting green TFP through the intermediate variable of resource allocation. We find that there is one single-threshold effect between LTM, resource allocation, and green TFP taking resource allocation as the threshold variable. Specifically, while the degree of resource mismatch is lower than 0.1371, the coefficient of LTM on green TFP is 0.1553; otherwise, the coefficient changes to −0.2776. This study concludes that LTM would significantly increase green TFP when the degree of regional resource mismatch is below the threshold; otherwise, it would have an inhibitory effect on the development of green TFP. In addition, the economic development level, R&D investment, and infrastructure level can, to a certain extent, contribute to the improvement of green TFP. The findings have three important policy implications for the land transfer policy of local governments, investment strategies of enterprises, and differentiated policy services.

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Section: Background and Conceptual Frameworkmentioning

confidence: 99%

Assessing the effects of land transfer marketization on green total factor productivity from the perspective of resource allocation: Evidence from China

Jin¹,

Lu²,

Gong³

2022

Front. Environ. Sci.

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“…Second, regarding the NK-DSGE model, there are various papers estimating this model for policy analysis in the developing and emerging economies [Liu and Zhang (2010), Gu et al (2014) and Dai et al (2015) for China; Elekdag et al (2005) and Choi and Hur (2015) for Korea; Sahminan et al (2017) and Gu et al (2014) for Indonesia; Ramayandi (2011) for four ASEAN countries such as Malaysia, Thailand, Indonesia and Philippines; Saxegaard et al (2010) and Gabriel et al (2016) for India; Silveira (2008) and Palma and Portugal (2014) for Brazil, Castillo et al (2013) for Peru, Medina and Soto (2007) for Chile and Steinbach et al (2009) for South Africa].…”

Section: Business Cycle Fluctuations In Vietnammentioning

confidence: 99%

The Vietnamese business cycle in an estimated small open economy New Keynesian DSGE model

Nguyen

2020

JES

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PurposeThe primary purpose of this paper is to investigate the sources of the business cycle fluctuations in Vietnam. To this end, the author develops a small open economy New Keynesian dynamic stochastic general equilibrium (SOE-NK-DSGE) model. Accordingly, this model includes various features, such as habit consumption, staggered price, price indexation, incomplete exchange-rate pass-through (ERPT), the failures of the law of one price (LOOP) and the uncovered interest rate parity. It is then estimated by using the Bayesian technique and Vietnamese data 1999Q1–2017Q1. Based on the estimated model, this paper analyzes the sources of the business cycle fluctuations in this emerging economy. Indeed, this research paper is the first attempt at developing and estimating the SOE-NK-DSGE model with the Bayesian technique for Vietnam.Design/methodology/approachA SOE-NK-DSGE model—Bayesian estimation.FindingsThis paper analyzes the sources of the business cycle fluctuations in Vietnam.Originality/valueThis research paper is the first attempt at developing and estimating the SOE-NK-DSGE model with the Bayesian technique for Vietnam.

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“…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%

“…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. 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 (2013), (2014), Dutu (2016), and Sahminan et al (2017). Aside from Dutu (2016), none of the existing studies considers inflation-target adjustmentsthey simply assume that the inflation target is constant.…”

Section: Related Literature and Contributionmentioning

confidence: 99%

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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A Dynamic Stochastic General Equilibrium (Dsge) Model to Assess the Impact of Structural Reforms on the Indonesian Economy

Cited by 8 publications

References 10 publications

Assessing the effects of land transfer marketization on green total factor productivity from the perspective of resource allocation: Evidence from China

Assessing the effects of land transfer marketization on green total factor productivity from the perspective of resource allocation: Evidence from China

The Vietnamese business cycle in an estimated small open economy New Keynesian DSGE model

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

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