Exchange Rate Volatility and Monetary Policy Shocks

The study investigated the influence of innovations in monetary policy on the rate of exchange volatility in Nigeria. The research adopted vector error correction model as well as impulse response function and forecast error variance decomposition function in the estimation using two models derived in the study. Monthly data between the periods 2009 and 2019 were adopted for the research. Our findings show that in the long run; all the monetary policy variables have a significant long run correlation with volatility in the exchange rate; but that money supply and the rate of exchange seem to have significant short run impact on volatility in the exchange rate, the other variables such as liquidity ratio or monetary policy rate did not show a significant short run relationship with the volatility in the exchange rate. Further findings on the volatility impulse response and the forecast error variance decomposition suggest a significant link between volatility in the exchange rate and money supply though the link was much more pronounced. The use of monthly data shows that the managed exchange rate regime by the CBN seems to have the desired effect in exchange rate volatility and thus having a critical impact on inflationary spikes.

The Linkage between Chittagong Stock Market and Dhaka Stock Market

This paper aims at determining the relationship between the two domestic stock markets of Bangladesh – the Chittagong Stock Market (CSE) and the Dhaka Stock Market (DSE). The daily stock price indices that represent the performance of the two stock markets are collected. In order to find out the interdependent relationship, the Engle-Granger Cointegration test, Granger Causality test, Impulse Response Function, and Variance Decomposition Analysis are employed in this paper. The main finding of this study is that both the stock markets are related in the long run. However, there is a one-way short-run effect from the DSE on the CSE market. The CSE market quickly responds to the shock in the DSE market. But, the DSE market is not responsive to the CSE market. The variance decomposition analysis shows that most of the shocks in the CSE market are explained by its own market. On the other hand, a small number of shocks in the DSE market are explained by the CSE market as well as its own market.

How and When Factors of Agricultural Contribution Influence Urbanization: A Historical Analysis of Tibet

Agriculture Powers Urbanization. How and when agriculture influences urbanization in underdeveloped regions remain poorly understood from an agricultural contribution perspective, specifically the food contribution (FDC), raw materials contribution (MLC), labor contribution (LRC), and market contribution (MTC). This study investigated this issue in the context of Tibet. A Granger causality test (GCT), the impulse response function (IRF), and variance decomposition (VD) were used. The GCT results demonstrated that agricultural contribution factors (ACFs), Granger-cause urbanization, and the IRF and VD results demonstrated that the influences of ACFs on urbanization were various and asynchronous. Both MTC and LRC quickly and positively respond to urbanization; however, LRC currently influences urbanization, whereas MTC influences urbanization currently and in the future. Both MLC and FDC negatively and slowly respond to urbanization; however, MLC currently influences urbanization, whereas FDC will influence urbanization in the future. This study’s findings depict changing trajectories of the role of ACFs in urbanization, elucidating urban–rural transformation.

Short and Long-Run Causal Effects of CO2 Emissions, Energy Use, GDP and Population Growth: Evidence from India Using the ARDL and VECM Approaches

This paper investigates the nexus between CO2 emissions (CO2E), GDP, energy use (ENU), and population growth (PG) in India from 1980–2018 by comparing the “vector error correction” model (VECM) and “auto regressive distributed lag” (ARDL). We applied the unit root test, Johansen multi-variate cointegration, and performed a Variance decomposition analysis using the Cholesky approach. The VECM and ARDL-bound testing approaches to cointegration suggest a long-term equilibrium nexus between GDP, energy use, population growth and CO2E. The empirical outcomes show the existence of a long-term equilibrium nexus between the variables. The Granger causality results show that short-term bi-directional causality exists between GDP and ENU, while a uni-directional causality between CO2E and GDP, CO2E and ENU, CO2E and PG, and PG and ENU. Evidence from variance decomposition indicates that 58.4% of the future fluctuations in CO2E are due to changes in ENU, 2.8% of the future fluctuations are due to changes in GDP, and 0.43% of the future fluctuations are due to changes in PG. Finally, the ARDL test results indicate that a 1% increase in PG will lead to a 1.4% increase in CO2E. Our paper addresses some important policy implications.

Analisis Pengaruh Kebijakan Bank Konvensional terhadap Tingkat Keuntungan Bank Syariah

Perkembangan perbankan syariah di Indonesia sangat pesat beberapa tahun belakangan ini. Namun, market share perbankan syariah masih jauh di bawah harapan. Kajian-kajian teori sebelumnya menyatakan bahwa lingkungan persaingan antar bank, dalam hal ini bank konvensional dan bank syariah, sangat mempengaruhi kinerja bank syariah. Penelitian ini ingin mengetahui bagaimana pengaruh kebijakan bank konvensional yang digambarkan dengan tingkat suku bunga (SB) terhadap keuntungan bank syariah yang digambarkan dengan Return on Assets (ROA). Metode analisis yang digunakan adalah Vector Autoregressive (VAR) dengan tambahan analisis Impulse Response Function (IRF) dan Variance Decomposition Analysis (VDC). Hasil analisis menggunakan VAR (1) menyatakan bahwa terdapat pengaruh negatif signifikan pada ) jika terjadi shock pada tingkat suku bunga tabungan bank konvensional (SB). Kondisi ini sejalan dengan hasil penelitian Haron dan Ahmad (2000); Haron (2004), serta Zainol dan Kassim (2012) yang mengemukakan bahwa apabila tingkat suku bunga tabungan bank konvensional meningkat, maka nasabah bank syariah akan beralih ke bank kovensional yang dianggap memberikan keuntungan lebih besar, sehingga keuntungan bank syariah mengalami penurunan. Hasil ini menunjukkan bahwa tidak semua konsumen bank syariah merupakan konsumen yang loyalis, perbankan syariah dituntut bertindak rasional, yaitu dengan cara menetapkan tingkat bagi hasil yang kompetitif terhadap tingkat suku bunga bank konvensional.

Causality between Foreign Remittance and Economic Growth: Empirical Evidence from Croatia

While human capital and foreign capital have received considerable attention in the study of economic growth, foreign remittances are less of a focus. Though some studies have identified the increasing importance of remittances, they have failed to analyze the relationship between foreign remittances and economic growth. The aim of this paper is to investigate the causal link between foreign remittances and economic growth in the Republic of Croatia over the period from 2000q1 to 2020q2. Any causal link is identified using Granger causality tests in vector autoregression models. In addition, variance decomposition and impulse response functions help determine any dynamic links. The empirical results suggest that, in the case of Croatia, there is a unidirectional causal relationship from foreign remittances to economic growth but no link in the opposite direction. The research results indicate that foreign remittances play a role in the Croatian economy and are one of the consequences of the large emigration processes that affected Croatia after joining the European Union.

Financial Frictions and Macroeconomy During Financial Crises: A Bayesian DSGE Assessment

The recent global financial crisis and the Eurozone sovereign default have rekindled the debate on the interactions between the real sector and the financial sphere. The present paper provides an assessment of the role of financial frictions on business cycles in Canada, the Euro Area, the U.K., and the U.S. during these recent financial crises using an extension of the DSGE methodology described by Merola (2015). The main goal is to examine whether and the extent to which those crises enhanced the contribution of financial frictions in driving macroeconomic fluctuations. The models’ properties are examined with posteriors distributions, variance decomposition, and historical decomposition. Posteriors distributions show that the role of real shocks in driving macroeconomic fluctuations decrease with the incorporation of financial frictions in the core DSGE model. Variance decomposition shows that financial frictions and financial shocks affect the business cycle through investment. The empirical estimates also suggest that the contribution of financial frictions and financial shocks in driving investment increases during the global financial crisis.

Interest Rate–Economic Growth Nexus Under Currency Board Operations

This paper analyses the effect of the prime interest rate as a monetary policy instrument to stimulate economic growth in Namibia, a small open economy that is constrained by currency board operations. A Vector Autoregressive Model (VAR) was used for the period 1980–2019. The result shows that Namibia’s prime interest rate has no significant effect on economic growth. This finding remains robust and consistent when impulse response function and variance decomposition are employed. The impulse response function indicates a shock on the prime interest rate exhibits an inverse relationship. However, this effect is insignificant in both short and long-run scenarios. The variance decomposition indicates that the prime interest rate has a strongly exogenous impact, implying it has a weak influence on GDP growth. Policy implication indicates that small open economies under currency board operations need to identify different policy responses to circumvent external shocks and addresses their development needs.

On Spurious Causality, CO2, and Global Temperature

Stips et al. (2016) use information flows (Liang (2008, 2014)) to establish causality from various forcings to global temperature. We show that the formulas being used hinge on a simplifying assumption that is nearly always rejected by the data. We propose the well-known forecast error variance decomposition based on a Vector Autoregression as an adequate measure of information flow, and find that most results in Stips et al. (2016) cannot be corroborated. Then, we discuss which modeling choices (e.g., the choice of CO2 series and assumptions about simultaneous relationships) may help in extracting credible estimates of causal flows and the transient climate response simply by looking at the joint dynamics of two climatic time series.