Narrow Results

The objective of this paper is to test the validity of two views of monetarism in Bangladesh, India, and Pakistan. A Structural Vector Autoregressive (SVAR) model is developed and the objective is accomplished by conducting Granger causality tests and estimating variance decompositions and impulse response functions. The first view of monetarism that changes in the quantity of money cause, lead and are positively related to changes in prices at least in the medium to long time horizon is supported in Bangladesh, India, and Pakistan. The second view of monetarism that changes in the quantity of money cause, lead and are positively related to changes in output at least in the short to medium time horizon is not supported. The implication of such a result is that an expansionary monetary policy only fuels prices with insignificant effects on output. It supports the view of real business cycle theorists who postulate that policy changes only affect prices.

The Fisher Effect postulated that real interest rate is constant, and that nominal interest rate and expected inflation move one-for-one together. This paper employs Johansen's method to investigate for the existence of a long-run Fisher effect in the Singapore economy over the period 1976 to 2006, and finds evidence of a positive relationship between nominal interest rate and inflation rate while rejecting the notion of a full Fisher Effect. The dynamic relationship between nominal interest rate and inflation rate is also examined from the error-correction models derived, and the analysis is extended to investigate the impulse response functions of inflation and nominal interest rates where we discover the presence of the Price Puzzle in the Singapore market.

We construct a realized volatility measure, using prices of daily West Texas Intermediate (WTI) crude oil futures and illustrate the robustness of this oil price volatility–macroeconomy relationship under a multivariate co-integrated vector autoregressive (VAR) model. Empirical results suggest that a spike in oil price volatility leads to investments and aggregate output to decline and inflation to rise over the period from 1983Q2 to 2009Q2. Furthermore, the gradual decline of Singapore's oil intensity signals a weakening relationship between oil price and the macroeconomy that supports our empirical findings.

The main purpose of this paper is to apply Johansen's vector error-correction model (VECM) to investigate the existence of the dividend signalling effect in the Singapore aggregate market through impulse response analysis, forecast error variance decomposition and Granger-causality test. Our findings show that a unit shock increase in dividend payout leads to a permanent increase in future earnings over time. These results imply that there exists informational/signalling content in dividend payout in the Singapore market over the long run. We further find that at least half of the forecast error variance in earnings can be accounted for by innovations in the dividend payout. In addition, the payout ratio is also shown to Granger-cause earnings in the Singapore market.

While the aggregate positive effects of entrepreneurship are assumed in many studies, there is a lack of empirical support for such assumptions. This study investigates the causal relationship between entrepreneurship, economic growth and unemployment. We also examine how a shock in one variable may influence other variables and the length of the effect. The findings of panel data from 39 countries collected between 2006 and 2016 using the Granger-causality test indicate a unidirectional causal effect of economic growth on entrepreneurship and unemployment. However, despite their correlation, no causal link was found between entrepreneurship and unemployment. The analysis of impulse-response functions also shows that only shocks from the entrepreneurship indicator are permanent in the model. Variance decomposition results reveal that the most important factor causing changes in entrepreneurship is the entrepreneurship indicator itself, implying that only specific entrepreneurial policies can affect the entrepreneurship indicator’s components and improve this indicator.

In the Ministerial meeting of ASEAN held in 1998, the devastation caused by Asian financial crisis remained the point of contemplation. The participants enthusiastically discussed the need to establish common currency and exchange rate system in order to counter any financial crisis anticipated. The ever-growing financial crisis threatening every region in the world has compelled the economists to acknowledge the elevating need of financial cooperation in their respective territories. This is certainly meant to ensure economic stability at both economic and political level. The authors, in the course of this paper, have focused the need to materialize the ideal of promoting monetary integration in the major economies of South, South East, and North East Asia. Calculating Optimum Currency Area (OCA) Index, the authors in a way present costs and benefits associated with the adoption of this currency union. Demand and supply sides of each economy are tested as a pre requisite of OCA in order to provide a good rationale in favor of selection of regions. For this purpose, Structural VAR Analysis (SVAR) method was employed and innovation accounting is done through variance decomposition of forecast errors, impulse response function and correlation matrix. The theory of OCA has been tested by (i) calculating the OCA index estimated by simple OLS method and (ii) following Bayoumi and Eichengreen extrapolating the variability of exchange rate data. The common consensus drawn from the two approaches adopted implies that there is a good potential in the region excluding China to construct a currency union particularly amongst South and North East Asian economies. It is worth mentioning, however, that some of these will have to work harder to join and become an effective member of this currency merger.

In this paper, we use the Vector Autoregression (VAR) approach to examine the robustness of the Phillips Curve in the United States economy from January 2020 to June 2022. The data is characterized by VAR(4) with a cointegrating rank of 2, using the unemployment rate and sticky inflation. The Impulse Response Function (IRF) is used to examine the relationship between the unemployment rate and inflation. The Granger-causal Test results suggest that historical unemployment data is useful for improving inflation projections. With a longer prediction horizon, unemployment shocks have a greater impact on the forecast error variance of inflation. Based on the impulse response function, the Phillips Curve is not alive in the US economy during the COVID-19 pandemic, but it can still be a significant factor legitimate for the government to set economic policy.