scholarly journals The Impact of Banking Policies to the Macroprudential Policy

JEJAK ◽  
2020 ◽  
Vol 13 (2) ◽  
pp. 367-380
Author(s):  
Desy Kharohmayani ◽  
Sudarso Kaderi Wiryono

The interaction between banks and macroeconomics is of crucial importance to financial stability. This study aims to answer the question of how macroeconomic shocks are transmitted to banking variables or vice versa. The study investigated the impact of the banking policies, the principal component of analysis (PCA) of banking quality indicators (CAMEL), and BI's rate to the aggregate of GDP and GDP priority sectors. The methodology used is the Factor Augmented Vector Autoregressive (FAVAR) model to observe the endogeneity of the observed variables. The results show that there is substantial heterogeneity in the transmission of macroeconomic shocks, caused by CAR, CAMEL and BI rate. In the short run, we find that the impulse response functions of aggregate GDP and GDP per sector of priority to the shock of the CAR decrease and close to zero in the long term. Our findings align with the expected effects that the CAMEL has implications to the decline of GDP of priority sector. Finally, we find that the impulse response of aggregate GDP and GDP of the priority sector to monetary policy shock decreases in the short run and near to zero in the more extended period

2022 ◽  
Vol 11 (1) ◽  
Author(s):  
Harry Aginta ◽  
Masakazu Someya

AbstractWe analyze how regional economic structures affect the impact of monetary policy on rates of inflation across 34 Indonesian provinces. The paper first applies structural factor augmented vector autoregressive model (SFAVAR) to all the 34 provinces based on monthly provincial data in order to measure the length and magnitude of responses of regional inflation to monetary policy shock, derived from the consequential impulse response functions of 34 provinces. In the second step, we analyze the impact of economic structures on the length and magnitude of regional inflationary responses of 34 provinces. We find that the impacts of monetary policy across regions are significantly influenced by economic structural variables such as manufacturing sector share to GDP, mining sector share to GDP, bank lending share to GDP and export share to GDP. In addition, we found the spatial lag, rate of inflation of neighboring provinces, is also statistically significant. In a similar fashion, economic structural variables such as manufacturing sector share to GDP, construction sector share to GDP and investment share to GDP are found statistically significant in explaining regional differences of monetary policy efficiency. Our findings imply economic structures of provinces have to be incorporated to designing monetary policy in Indonesia.


Author(s):  
Mark A. Thoma ◽  
Wesley W. Wilson

Time series techniques—particularly impulse–response functions and variance decompositions—are used to characterize the short-run relationships between 17 variables in a vector autoregressive model designed to trace the short-run interconnections among variables affecting lockages on the Mississippi and Illinois Rivers. The model contains five categories of variables: lockages, barge rates, grain bids, rail rates, and rail deliveries. Variance decompositions are constructed that identify barge rates as the most important variable affecting lockages at both short and long horizons. Barge rates are, in turn, explained largely by lockages and rail rates, indicating two-way feedback or bidirectional causality between lockages and barge rates. Impulse–response functions are also examined. The variance decompositions indicate that barge rates are important in explaining lockages, and the impulse–response functions show how lockages and other variables respond to such shocks. In general, there is a substitution away from barge transportation and toward rail transportation when barge rates increase. The results are useful for illuminating the causal relationships among variables in the model and for understanding behavioral relationships present in the data and can be used to guide short- and long-run planning models. For example, many planning models assume that barge traffic does not respond significantly to changes in barge rates; however, results obtained here imply that barge traffic and rail deliveries do respond to such changes. This potentially important implication illustrates the usefulness of the time series techniques used.


2017 ◽  
Vol 2 (2) ◽  
pp. 55-70 ◽  
Author(s):  
Ai Nur Bayinah

This paper is aimed to assess the contribution of Zakat in boosting Islamic banks’ financing and economic growth for the period 2011-2015, in 10 district/city of West Java Province, Indonesia. Through Vector Autoregressive (VAR) panel co-integration analysis, variance decompositions (VD) and impulse response functions (IRF), this study investigates Zakat, Islamic Banking, and economic growth nexus. Findings in this research highlight that Zakat has a significant impact on Islamic banking, so this institution would contribute to economic growth both in the short and the long run, with fluctuation in variance from the first year. The results lend support to the view that Zakat not only leads to social benefits but also has a positive impact on the economy through increasing Islamic banks’ financing. Therefore, this research will serve as a motivation for the industry players and regulators to continuously promote Zakat as a strategic policy. The originality of this research is to assess Zakat-led growth and finance by analyzing the impact of Zakat on the Islamic banking and regional economic outcome. Another novel aspect of this study is in the methodology as it employs VAR panel co-integration analysis, VDs and IRFs on the set of annual data. Keywords: Zakat, Islamic Banking Financing, Economic Growth, West Java


2018 ◽  
Vol 9 (1) ◽  
pp. 17-44 ◽  
Author(s):  
Rosylin Mohd Yusof ◽  
Farrell Hazsan Usman ◽  
Akhmad Affandi Mahfudz ◽  
Ahmad Suki Arif

Purpose This study aims to investigate the interactions among macroeconomic variable shocks, banking fragility and home financing provided by conventional and Islamic banks in Malaysia. Identifying the causes of financial instability and the effects of macroeconomic shocks can help to foil the onset of future financial turbulence. Design/methodology/approach The autoregressive distributed lag bound-testing cointegration approach, impulse response functions (IRFs) and forecast error variance decomposition are used in this study to unravel the long-run and short-run dynamics among the selected macroeconomic variables and amount of home financing offered by both conventional and Islamic banks. In addition, the study uses Granger causality tests to investigate the short-run causalities among the selected variables to further understand the impact of one macroeconomic shock to Islamic and conventional home financing. Findings This study provides evidence that macroeconomic shocks have different long-run and short-run effects on amount of home financing offered by conventional and Islamic banks. Both in the long run and short run, home financing provided by Islamic banks is more linked to real sector economy and thus is more stable as compared to home financing provided by conventional banks. The Granger causality test reveals that only gross domestic product (GDP), Kuala Lumpur Syariah Index (KLSI)/Kuala Lumpur Composite Index (KLCI) and house price index (HPI) are found to have a statistically significant causal relationship with home financing offered by both conventional and Islamic banks. Unlike the case of Islamic banks, conventional home financing is found to have a unidirectional causality with interest rates. Research limitations/implications This study has focused on analyzing the macroeconomic shocks on home financing. However, this study does not assess the impact of financial deregulation and enhanced information technology on amount of financing offered by both conventional and Islamic banks. In addition, it is not within the ambit of this present study to examine the effects of agency costs and information asymmetry. Practical implications The analysis of cointegration and IRFs exhibits that in the long run and short run, home financing provided by Islamic banks are more linked to real sector economy like GDP and House Prices (HPI) and therefore more resilient to economic vulnerabilities as compared to home financing provided by conventional banks. However, in the long run, both conventional and Islamic banks are more susceptible to fluctuations in interest rates. The results of the study suggest that monetary policy ramifications to improve banking fragility should focus on stabilizing interest rates or finding an alternative that is free from interest. Social implications Because interest plays a significant role in pricing of home loans, the potential of an alternative such as rental rate is therefore timely and worth the effort to investigate further. Therefore, Islamic banks can explore the possibility of pricing home financing based on rental rate as proposed in this study. Originality/value This paper examines the unresolved issues in Islamic home financing where Islamic banks still benchmark their products especially home financing, to interest rates in dual banking system such as in the case of Malaysia. To the best of the authors’ knowledge, studies conducted in this area are meager and therefore is imperative to be examined.


The empirical analysis of this chapter provides insights into the functioning of the economies of three selected countries. Later in the chapter, the dynamic responses of the model to shocks in indicators of financial development are investigated. To obtain credible impulse response analysis, economic theory is used to set the required identifying restrictions instead of using an “unrestricted” vector autoregressive model. The structural form of the model then is summarised in the chapter by the variance decomposition and impulse response functions. The general results from impulse response functions advocate the theory of financial intermediation arguing that the development of the financial market helps to promote economic growth. Furthermore, the results of variance decomposition shows that different measures of financial development influence the variation of growth variables, particularly investment, savings, and productivity growth.


1994 ◽  
Vol 1 (3) ◽  
pp. 267-278 ◽  
Author(s):  
Hyungsoon Park ◽  
Youn-sik Park

The impulse response functions (force-strain relations) for Euler–Bernoulli and Timoshenko beams are considered. The response of a beam to a transverse impact force, including reflection at the boundary, is obtained with the convolution approach using the impulse response function obtained by a Laplace transform and a numerical scheme. Using this relation, the impact force history is determined in the time domain and results are compared with those of Hertz's contact law. In the case of an arbitrary impact, the location of the impact force and the time history of the impact force can be found. In order to verify the proposed algorithm, measurements were taken using an impact hammer and a drop test of a steel ball. These results are compared with simulated ones.


2016 ◽  
Vol 34 (5) ◽  
pp. 432-456 ◽  
Author(s):  
Jonas Hahn ◽  
Verena Keil ◽  
Thomas Wiegelmann ◽  
Sven Bienert

Purpose – The purpose of this paper is to estimate the impact of changes in macro-economic conditions going forward, focusing on a change in interest policy, with regard to office letting and investment markets. Design/methodology/approach – For this analysis, the authors constructed two vector-autoregressive models, measuring the response of office rents and capital values in Germany to economic impulses. The authors isolated effects of unique exogenous positive shocks (such as economic growth or interest leaps) on the basis of impulse-response functions in order to understand the complex dynamic interdependence between several economic factors and office performance changes. Findings – The authors initially find a moderately positive development of both office performance components even although supposing an increase in interest level. In terms of capital values, the authors find that they do not drop before 1.5 years after the interest impulse and the negative effect peaks after approximately nine quarters. Furthermore, the reaction to a change in GDP is significantly lower than a reaction to the interest rate, but impulses in other macro-economic factors provoke stronger reactions. Finally, the authors find that a positive interest shock leads to a comparably robust development and economic sustainability in office rents throughout a consideration horizon of 24 quarters. Research limitations/implications – Estimations are based on observations from a time period containing two rather extraordinary market phases. As they included bubble growth and the low-interest environment, the authors find that certain patterns in both phases neutralize each other when looking at the total time frame. The authors constructed sub-samples to compensate for this. However, the research does not provide to what extent the measured impulse-responses stay forecast-proof, if the market moves into a phase of short-term normalization. Practical implications – This paper provides insights into estimated impulse-response patterns on a hypothetical sudden increase of several macro-economic determinants. On this basis, the probable reaction to an increase in, for example, the interest rate level can be approximated. Also, the paper provides a fundamental understanding of the economic sustainability of German office properties in terms of their value and rent performance in the case of exogenous shocks. Originality/value – This paper contains the first vector-autoregressive, impulse-response analysis of office markets in Germany in the context of several macro-economic drivers, including the interest level. It delivers insights into market reaction patterns on the basis of simulated one standard deviation shocks in all included variables.


2013 ◽  
Vol 4 (2) ◽  
pp. 267-286 ◽  
Author(s):  
D. J. L. Olivié ◽  
G. P. Peters

Abstract. Emission metrics are used to compare the climate effect of the emission of different species, such as carbon dioxide (CO2) and methane (CH4). The most common metrics use linear impulse response functions (IRFs) derived from a single more complex model. There is currently little understanding on how IRFs vary across models, and how the model variation propagates into the metric values. In this study, we first derive CO2 and temperature IRFs for a large number of complex models participating in different intercomparison exercises, synthesizing the results in distributions representing the variety in behaviour. The derived IRF distributions differ considerably, which is partially related to differences among the underlying models, and partially to the specificity of the scenarios used (experimental setup). In a second part of the study, we investigate how differences among the IRFs impact the estimates of global warming potential (GWP), global temperature change potential (GTP) and integrated global temperature change potential (iGTP) for time horizons between 20 and 500 yr. Within each derived CO2 IRF distribution, underlying model differences give similar spreads on the metrics in the range of −20 to +40% (5–95% spread), and these spreads are similar among the three metrics. GTP and iGTP metrics are also impacted by variation in the temperature IRF. For GTP, this impact depends strongly on the lifetime of the species and the time horizon. The GTP of black carbon shows spreads of up to −60 to +80% for time horizons to 100 yr, and even larger spreads for longer time horizons. For CH4 the impact from variation in the temperature IRF is still large, but it becomes smaller for longer-lived species. The impact from variation in the temperature IRF on iGTP is small and falls within a range of ±10% for all species and time horizons considered here. We have used the available data to estimate the IRFs, but we suggest the use of tailored intercomparison projects specific for IRFs in emission metrics. Intercomparison projects are an effective means to derive an IRF and its model spread for use in metrics, but more detailed analysis is required to explore a wider range of uncertainties. Further work can reveal which parameters in each IRF lead to the largest uncertainties, and this information may be used to reduce the uncertainty in metric values.


2020 ◽  
Vol 7 (6) ◽  
pp. 1
Author(s):  
Ralf Fendel ◽  
Nicola Mai ◽  
Oliver Mohr

This paper examines the role of uncertainty in the context of the business cycle in the euro area. To gain a more granular perspective on uncertainty, the paper decomposes uncertainty along two dimensions: First, we construct the four different moments of uncertainty, including the point estimate, the standard deviation, the skewness and the kurtosis. The second dimension of uncertainty spans along three distinct groups of economic agents, including consumers, corporates and financial markets. Based on this taxonomy, we construct uncertainty indices and assess the impact on real GDP via impulse response functions and further investigate their informational value in rolling out-of-sample GDP forecasts. The analysis lends evidence to the hypothesis that higher uncertainty expressed through the point estimate, a larger standard deviation among confidence estimates, positive skewness and a higher kurtosis are all negatively correlated with the business cycle. The impulse response functions reveal that in particular the first and the second moment of uncertainty cause a permanent effect on GDP with an initial decline and a subsequent overshoot. We find uncertainty in the corporate sector to be the main driver behind this observation, followed by financial markets’ uncertainty whose initial effect on GDP is comparable but receding much faster. While the first two moments of uncertainty improve GDP forecasts significantly, both the skewness and the kurtosis do not augment the forecast quality any further.


2019 ◽  
Vol 11 (10) ◽  
pp. 2776 ◽  
Author(s):  
Rangan Gupta ◽  
Zhihui Lv ◽  
Wing-Keung Wong

Unlike the existing literature, which primarily studies the impact of only monetary policy shocks on real estate investment trusts (REITs), this paper develops a change-point vector autoregressive (VAR) model and then analyzes, for the first time, regime-specific impact of demand, supply, monetary policy, and spread yield shocks, identified using sign-restrictions, on US REITs returns. The model first isolates four major macroeconomic regimes in the US since the 1970s and discloses important changes to the statistical properties of REITs returns and its responses to the identified shocks. A variance decomposition analysis revealed aggregate supply shocks to have dominated in the early part of the sample period, and monetary policy and spread shocks at the end. Our results imply that ignoring other possible shocks in the model is likely to lead to incorrect inferences, and over-reliance on (conventional) monetary policy in correcting for possible bubbles in the REITs sector, which it will fail to rectify, given the importance of other shocks driving the REITs sector.


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