Regional economic structure and heterogeneous effects of monetary policy: evidence from Indonesian provinces

We 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.

Impact of fiscal and monetary policy on economic growth in Vietnam

This paper uses the Johansen cointegration test and the Vector Error Correction Model (VECM) to study the impact of fiscal and monetary policy on economy growth in Vietnam during the period from quarter I/2004 to quarter II/2013. The results showed the cointegration relation between the macroeconomic policies and economic growth. Besides, the variance decomposition and impulse response functions from VECM model showed the impact of the two policies on economic growth were limited, in which the impact of the monetary policy on growth is greater than that of the fiscal policy on growth. Subsequently, the paper provides some recommendations to improve the efficiency of the implementation of these policies in Vietnam.

Impact of tourism development on inclusive growth: A panel vector autoregression analysis for African economies

The persistent debate among policy makers and academics around combating the high rates of poverty and income inequality can be further illuminated by understanding how tourism contributes to inclusive growth, especially in developing economies. Tourism sector can be regarded as one of the key contributors to inclusive growth and where it has the capacity to generate prospects for productive employment. The goal of this article is thus to investigate the link between inclusive growth and tourism in the African context. To do this, we utilized a recent panel vector autoregression (pVAR) and data for 45 African countries spanning the period 1995 to 2019. Thus, by the error variance decomposition and impulse response functions, our results showed a weak positive effect of international tourism arrivals and the composite tourism indicator on inclusive growth, while tourism receipts and tourism expenditure insignificantly decreases inclusive growth in the sampled African economies. Our result is further supported by the panel system generalized method of moments (GMM). We provide some policy implications from our findings.

Mechanism Study on the Impact of China Population Structure Change on the Water Use of the Three Main Industries

As the principal part of economic and social development, the demographic factor is the fundamental factor driving the change of water resources, and achieving the harmony of human and water has been one of the most important tasks to promote high-quality development. Based on Maslow’s hierarchy of needs theory, this article applied panel data for 19 years and employed impulse response functions and threshold models to do a mechanism analysis of the impact of population structure changes on the water consumption changes of the three main industries. The study found the following: Firstly, the urban population promotes an increase of the total water consumption, industrial water consumption, and domestic water consumption, which suppresses agricultural water consumption and shows an inverted “N” trend. Secondly, the aging population has expanded the total water consumption, and agricultural and domestic water demand, and reduced industrial water consumption. Thirdly, food consumption helps to reduce the total water consumption and agricultural water consumption, but increases the industrial water consumption and the growth rate rises. Fourthly, the increase in the proportion of agricultural employment reduces the total water consumption, and agricultural and domestic water consumption, and increases industrial water consumption. Fifthly, the total water consumption and domestic water consumption both increase with the improvement of the population education level, while the agricultural water consumption declines first and then rises. The empirical results can provide a reference for analyzing the driving mechanisms of regional water consumption changes.

Stock Market Reactions during Different Phases of the COVID-19 Pandemic: Cases of Italy and Spain

The COVID-19 pandemic and pandemic-induced lockdowns and quarantine establishments have inevitably affected individuals, businesses, and governments. At the same time, the spread of the COVID-19 pandemic had a dramatic impact on financial markets all over the world and caused an increased level of uncertainty; the stock markets were no exception either. Most of the studies on the impact of the COVID-19 pandemic on stock markets are based either on the analysis of a relatively short period (the beginning of pandemic) or a longer period, which, in turn, is very heterogeneous in terms of both the information available on the COVID-19 virus and the measures taken to contain the virus and address the consequences of the pandemic. However, it is very important to assess the impact not only at the beginning of the pandemic but also in the subsequent periods and to compare the nature of this impact; the studies of this type are still fragmentary. Therefore, this research aims to investigate the impact of the COVID-19 pandemic on stock markets of two of the most severely affected European countries—Italy and Spain. To reach the aim of the research OLS regression models, heteroscedasticity-corrected models, GARCH (1,1) models, and VAR-based impulse response functions are employed. The results reveal that the stock market reaction to the spread of the COVID-19 pandemic differs depending on the country and period analyzed: OLS regression and heteroscedasticity-corrected models have not revealed the statistically significant impact of the spread of the COVID-19 pandemic, while impulse response functions demonstrated the non-zero primary response of analyzed markets to the COVID-19 shock, and GARCH models (in the case of Spain) confirmed that the COVID-19 pandemic increased the volatility of stock market return. This research contributes to the literature by providing a comprehensive impact assessment both during the whole pre-vaccination period of the pandemic and during different stages of this period.

Estimating Impulse-Response Functions for Macroeconomic Models using Directional Quantiles

A multivariate vector autoregressive model is used to construct the distribution of the impulse-response functions of macroeconomics shocks. In particular, the paper studies the distribution of the short-, medium-, and long-term effects after a shock. Structural and reduced form quantile vector autoregressive models are developed where heterogeneity in conditional effects can be evaluated through multivariate quantile processes. The distribution of the responses can then be obtained by using uniformly distributed random vectors. An empirical example of exchange rate pass-through in Argentina is presented.

Has the EU-ETS Financed the Energy Transition of the Italian Power System?

This paper focuses on the relationship between the European Union Emission Trading System allowances’ prices and the Italian electricity price, aiming at assessing whether such a mechanism has been a driver for the decarbonization of the power sector. To this aim, we calculate the long-run relationships between energy prices, natural gas prices and allowances’ prices, through a VECM model, distinguishing between peak and off-peak prices. The analysis is carried out for the third phase of the EU-ETS, which started in 2013, and for two-year rolling windows that account for changes over time of the pass-through rates. It is shown that the natural gas price has a high pass-through rate of roughly 70%, which is increasing over time. On the contrary, the pass-through rate of the allowances’ price is as low as 7% for the wholesale electricity price, being slightly more and less for the peak and off-peak prices, respectively. However, this rate has been substantially changing over time, starting from a high level and falling significantly, becoming negative in the recent years. This could signal that the EU-ETS has been increasingly more effective in endogenizing emission costs for power producers, inducing them to reduce their production costs associated with emissions by means of a change in technologies. However, the analysis of the impulse response functions hardly supports this finding, eventually casting doubts on the effectiveness of the EU-ETS in Italy to drive the transition toward a less carbon-intensive power supply.

VALIDATING DSGE MODELS WITH SVARS AND HIGH-DIMENSIONAL DYNAMIC FACTOR MODELS

A popular validation procedure for Dynamic Stochastic General Equilibrium (DSGE) models consists in comparing the structural shocks and impulse-response functions obtained by estimation-calibration of the DSGE with those obtained in an Structural Vector Autoregressions (SVAR) identified by means of some of the DSGE restrictions. I show that this practice can be seriously misleading when the variables used in the SVAR contain measurement errors. If this is the case, for generic values of the parameters of the DSGE, the shocks estimated in the SVAR are not “made of” the corresponding structural shocks plus measurement error. Rather, each of the SVAR shocks is contaminated by noncorresponding structural shocks. We argue that High-Dimensional Dynamic Factor Models are free from this drawback and are the natural model to use in validation procedures for DSGEs.

THE INFLUENCE OF FORWARD SPEED AND NONLINEARITIES ON THE DYNAMIC BEHAVIOUR OF A CONTAINER SHIP IN REGULAR WAVES

The aim of this paper is to compare the heave and pitch motions for the S175 containership, travelling in head regular waves, obtained from frequency domain linear and time domain partly nonlinear potential flow analyses. The frequency domain methods comprise the pulsating and the translating, pulsating Green’s function methods, with the relevant source distribution over the mean wetted surface of the hull. The time domain method uses the radiation and diffraction potentials related to the mean wetted surface, implemented using Impulse Response Functions (IRF), whilst the incident wave and restoring actions are evaluated on the instantaneous wetted surface. The calculations are carried out for a range of Froude numbers, and in the case of the partly nonlinear method for different wave steepness values. Comparisons are made with available experimental measurements. The discussion focuses on the necessity for a nonlinear approach for predicting the radiation potential and the possible numerical methods for its formulation.

Disagreement on expectations: firms versus consumers

This paper evaluates the dynamic response of economic activity to shocks in agents’ perception of uncertainty. The study focuses on the comparison between manufacturers’ and consumers’ perception of economic uncertainty, gauged by a geometric discrepancy indicator to quantify the proportion of disagreement in eleven European countries and the Euro Area. A vector autoregressive framework is used to estimate the impulse response functions to innovations in disagreement, both for manufacturers and consumers. The effect on economic activity of shocks to the perception of uncertainty is found to differ markedly between both types of agents. On the one hand, shocks to consumer discrepancy tend to be of greater magnitude and duration than those to manufacturer discrepancy. On the other hand, innovations in disagreement between the two collectives have an opposite effect on economic activity: shocks to manufacturer discrepancy lead to a decrease in economic activity, as opposed to shocks to consumer discrepancy. This finding is of particular relevance to researchers when using cross-sectional dispersion of survey-based expectations for approximating and assessing economic uncertainty, since the effect on economic growth of shocks to disagreement may be dependent on the type of agent and the way in which expectations have been elicited.