External and Internal Shocks and the Movement of Palm Oil Price: SVAR Evidence from Malaysia

Movements in palm oil price give important signals to various stakeholders of the palm oil industry in Malaysia. Thus, understanding external and internal factors that may affect the palm oil price is vital to the industry players for sustainability of their activities. This study investigates relative importance of external and internal shocks on the movement of palm oil price in Malaysia. Employing a structural vector autoregressive (SVAR) model on quarterly data from 1990 to 2019, the findings reveal that external shocks are more dominant in affecting the palm oil price. Shocks to the crude oil price, the prices of substitution goods (soybeans oil, rapeseed oil, and sunflower oil), the world palm oil price, and foreign income significantly affect the palm oil price in the short and medium run. The results also indicate that a shock to soybean oil price has a more profound effect on the palm oil price than a shock to rapeseed oil or sunflower oil prices, respectively. Likewise, shocks to incomes from India as well as from Netherlands create greater impacts on the palm oil price than a shock to income from the other trading partners, respectively. The study has shown the importance of external factors in affecting the palm oil industry.

How Does Fiscal Policy Affect Bank Credit? Evidence from China

Using a set of Chinese economic data and a structural vector autoregression (SVAR) model, this paper investigates the transmission channels of fiscal policy to bank credit in China. We find that increases in tax revenue can increase bank credit through external financing premium channel, collateral channel, and bank liquidity channel. We also find that increases in government spending can reduce bank credit through bank liquidity channel and increase bank credit through external financing premium channel and collateral channel.

Does Emigration Hurt the Economy? Evidence from Lithuania

This study explores the economic impact of population emigration with special reference to the case of Lithuania. For this reason, we developed a SVAR model and applied related IRF and FEVD tools using quarterly data for the period of 2001-2020. Our findings reveal that a positive shock in emigration is related to lower unemployment. It is also found that the increased emigration is linked to higher real wage growth but with a lower confidence interval. Moreover, our estimates suggest that international out-migration increases real GDP growth in the short term, with no significant effects in the long run perspective. Finally, we found that most of the emigrants-to-be were inactive for a long term prior to departure, which offers a new look into the consequences of Lithuanian emigration, suggesting that the economic losses of emigration could be overstated. This study contributes to the knowledge about the impact of emigration on the economy and specifies directions for further studies in the field.

The relationship between LNG price, LNG revenue, non-LNG revenue and government spending in China: An empirical analysis based on the ARDL and SVAR model

The present paper examines the dynamic relationship between liquefied natural gas (LNG) price, LNG revenue, non-LNG revenue and government spending (GOVS) in China using autoregressive distributed lag (ARDL) and structural vector auto-regressive (SVAR) model. The goal of carrying out ARDL and SVAR together is to consolidate and strengthen the consistency of the results obtained from both approaches. ARDL results show that a positive influence relationship between both short-run and long-run LNG prices, LNG revenue, non-LNG revenue and GOVS, but there was no significant relationship between LNG price and GOVS. The SVAR also substantiates the results of ARDL test and provides further insight which shows that long-run fiscal synchronization hypothesis is evidenced between the LNG revenue and GOVS, while spend-tax hypothesis exists in the long-run between GOVS and non-LNG revenue. It is also evidenced that there is a complementary relationship between LNG revenue and non-LNG revenue, but this complementary role is stronger than the substitution role. Since non-LNG revenue has a greater impact on GOVS in the short-run, and the impact of LNG prices and LNG revenue on GOVS in the long-run increases over time, thus, GOVS mitigates the direct impact of non-LNG revenue to some extent, and that an appropriate allocation of spending in the non-LNG industry will have a positive impact on the development of the market economy supporting the Keynesian and spend-tax hypothesis.

The Dynamic Impact of Structural Oil Price Shocks on the Macroeconomy

In this paper, we apply the structural vector autoregression (SVAR) model to decompose the international oil price shock into oil supply shocks, aggregate demand shocks and oil-specific demand shocks, and then use the DCC-GARCH model to analyse the dynamic correlations between these three kinds of oil price shocks and the macroeconomic variables of several oil importing and exporting countries. To quantify the intensity of the effect of oil shocks on these variables, we propose a measure, conditional expectation (CoE), to capture the percent change of the economic variable under oil price shocks relative to the median state. The time-varying copula model is employed to estimate the proposed measure through time. The empirical results show that, for instance, the impacts of oil price shocks on macroeconomic variables are different in different periods, showing the time-varying characteristics. Additionally, the impacts of oil price shocks on macroeconomic variables show great differences and some similarities among different countries. Finally, we give some policy suggestions for these countries, in particular for China’s special results.

Assessing the Financial Implications of COVID-19 Within the SVAR Framework for Some Asian Countries

This article examines the structural responses of foreign exchange and equity markets to the COVID-19 pandemic in seven Asian countries over its first 4 months (31 December 2019 to 1 May 2020). Marginal effects derived from a structural vector autoregression (SVAR) model suggest that a 1% increase in incidence of COVID-19 cases significantly diminished Indonesia’s equity market returns by 4.7%, depreciated the Indian rupee against the US dollar by 4.8%, but improved equity prospects in South Korea by 4.1%. For the other financial markets, the effect of COVID-19 was found to be insignificant. Further, the impulse response analyses imply that the influence of COVID-19 on foreign exchange and equity markets is only transitory in nature. Additional SVAR analysis for India and Indonesia over recent months (2 May 2020 to 22 January 2021) showed that their financial markets remained (or became) resistant to the escalating incidence of COVID-19 inflections and deaths. JEL Code: G15

ASSESSMENT OF THE PANDEMIC SHOCK ON THE TOURISM SECTOR - THE CASE OF CROATIA

Due to the pandemic crisis, the decline in cross-border travel has caused deterioration of consumption and induced the collapse of domestic consumption. Finally, the drop of the consumption in travel service affected the travel trade balance and caused decline of the economy. The aim of this paper is to analyze the impact of the pandemic shock on the touristic sector in Croatia and to measure the effect of this negative trend. The research will be conducted using the SVAR model to disclose pandemic shock. The analysis considers the effect of the pandemic shock on the performance of the tourism sector, what is approximated by CROBEX turist index. Also, the analysis tests the impact of pandemic shock on turnover of the hotel industry. The results confirm the large-scale shock in the touristic sector and implicate the importance of measuring shock in assessing future trends and proposing measures for economic recovery in Croatia.

NEWS SHOCKS AND THE EFFECTS OF MONETARY POLICY

Traditionally identified monetary shocks in a structural vector autoregression (SVAR) model typically result in long-lasting effects on output and total factor productivity (TFP). In this paper, I argue that the typical monetary shock has been confounded with the news shock about future technology. I propose and implement a novel SVAR approach that effectively “cleans” the technology component from the traditional Cholesky monetary shock. With the new identification, I find that a monetary shock exerts smaller and less persistent effects on output and the level of measured TFP than a traditionally identified monetary shock. Finally, I show that the SVAR impulse responses can be replicated by augmenting the standard New Keynesian model with a time-varying inflation target and a non-Ricardian fiscal policy regime.