Forecasting crude oil prices with DSGE models

In this study, we conducted an oil prices forecasting competition among a set of structural models, including vector autoregression and dynamic stochastic general equilibrium (DSGE) models. Our results highlight two principles. First, forecasts should exploit the fact that real oil prices are mean reverting over long horizons. Second, models should not replicate the high volatility of the oil prices observed in samples. By following these principles, we show that an oil sector DSGE model performs much better at real oil price forecasting than random walk or vector autoregression.     

The effects of oil price shocks on job reallocation

We investigate the effect of oil price innovations on U.S. manufacturing job flows using a simultaneous equation model that nests symmetric and asymmetric responses. We find no evidence of asymmetry in the response of job flows to positive and negative oil price innovations. We then inquire whether firms, when facing positive shocks, shed jobs faster than they create jobs. We show that positive innovations lead to a decline in net employment and an increase in job reallocation, possibly due to search and matching issues. Yet, the latter effect becomes statistically insignificant when we control for data mining. We demonstrate that the cumulative one-year effect of oil price shocks on job creation and destruction was smaller during the Great Moderation, but it was larger for gross job reallocation. These variations were caused by a change in the transmission channel and not by smaller oil price shocks.     

The time varying effect of oil price shocks on euro-area exports

In this paper we provide novel evidence on changes in the relationship between the real price of oil and real exports in the euro area. By combining robust predictions on the sign of the impulse responses obtained from a theoretical model with restrictions on the slope of the oil demand and oil supply curves, we identify oil supply and foreign productivity shocks in a time varying VAR with stochastic volatility. We find that from the 1980s onwards the relationship between oil prices and euro area exports has become less negative conditional on oil supply shortfalls and more positive conditional on foreign productivity shocks. Using the theoretical model we show that our empirical findings can be accounted for by (i) stronger trade relationship between the euro area and emerging economies (ii) a decrease in the share of oil in production and (iii) increased competitive pressures in the product market.     

Investigating properties of commodity price responses to real and nominal shocks

This paper studies dynamic adjustments of 49 world commodity prices in response to innovations in the nominal exchange rate and the world real GDP. After we estimate the dynamic elasticity of the prices with respect to these shocks, we obtain the kernel density of our estimates to establish stylized facts on the adjustment process of the commodity price toward a new equilibrium path. Our empirical findings imply, on average, that the law of one price holds in the long-run, whereas the substantial degree of short-run price rigidity was observed in response to the nominal exchange rate shock. The real GDP shock tends to generate substantial price fluctuations in the short-run because adjustments of the supply can be limited, but have much weaker effects in the long-run as the supply eventually counterbalances the increase in the demand. Overall, we report persistent long-lasting effects of the nominal exchange rate shock on commodity prices relative to those of the real GDP shock.     

Exchange rate dynamics and their effect on macroeconomic volatility in selected CEE countries

To understand the potential for forming an optimum currency area it is important to investigate the origins of macroeconomic volatility. We focus on the contribution of real exchange rate shocks to macroeconomic volatility in selected Central and Eastern European countries. The contribution of real exchange rate shocks relative to other shocks allows us to evaluate whether the real exchange rate is a source of volatility or a buffer against shocks, as the theory suggests. The identification of the contributions is based on variance decomposition in two-country structural VAR models, which are identified by the sign restriction method. For most of the countries in the sample, shocks are predominantly symmetric relative to their effective counterpart, although the role of non-symmetric shocks is non-negligible. In general, for all the countries considered except Bulgaria and Slovenia, the real exchange rate does not generate large volatility over the business cycle and, with the exception of Bulgaria and Romania, is mostly driven by the non-symmetric shocks. These results are consistent with the real exchange rate having a shock-absorbing nature.     

The effects of oil price shocks on inflation in the G7 countries

This study examines the effects of three types of oil price shocks on inflation in the G7 countries with a new method of isolating oil price shocks. Based on monthly data from January 1997 to January 2019, we find that each oil price shock has the largest effect on U.S. inflation among the G7 countries and each country’s response to oil price shocks is different. Moreover, a rolling-window analysis shows that supply shocks, demand shocks and risk shocks have dynamic effects on inflation. The effect of supply shocks on inflation is strong before the financial crisis, but weakens during the crisis. However, the effect of demand shocks increases sharply in this time. The effect of risk shocks mainly occurs during the financial crisis and the European debt crisis. In addition, this study uses two ways to verify the robustness of the results. Our empirical results have important implications for policymakers and manufacturers, since the results provide a good explanation for the response of inflation in the G7 countries to the oil price shocks from different sources.     

The nonlinear effect of oil price shocks on financial stress: Evidence from China

This paper examines the nonlinear effects of different types of oil price shocks on China’s financial stress index (FSI). For this purpose, we use newly proposed framework by Ready (2018) to decompose oil prices into supply, demand and risk shocks. Then, we use a Markov regime-switching (MRS) model to investigate the nonlinear effects of these oil price shocks on China’s FSI. The empirical results show that the effects of three oil price shocks are nonlinear under different regimes. In particular, oil supply shocks mainly have a significantly positive effect on China’s FSI in the low-volatility state; demand shocks have negative effects on China’s FSI in different regimes, but this effect is larger in the low-volatility state; the effect of risk shocks on China’s FSI is the opposite, and it is positive in the high-volatility state but negative in the low-volatility state.     

The price responsiveness of housing supply in OECD countries

The responsiveness of housing supply to changes in prices bears important implications for the evolution of housing prices and the speed of adjustment of housing markets. Based on a stock-flow model of the housing market estimated within an error correction framework, this paper estimates the long-run price elasticity of new housing supply in 21 OECD countries. Estimates suggest that the responsiveness of housing supply to price changes varies substantially across countries. It is relatively more flexible in North America and some Nordic countries, while it is more rigid in continental European countries and in the United Kingdom. The responsiveness of housing supply depends not only on national geographical and urban characteristics but also on policies, such as land use and planning regulations.     

The dynamic impact of oil price shocks on the stock market and the USD/RMB exchange rate: Evidence from implied volatility indices

Using daily data from March 16, 2011, to September 9, 2019, we explore the dynamic impact of the oil implied volatility index (OVX) changes on the Chinese stock implied volatility index (VXFXI) changes and on the USD/RMB exchange rate implied volatility index (USDCNYV1M) changes. Through a TVP-VAR model, we analyse the time-varying uncertainty transmission effects across the three markets, measured by the changes in implied volatility indices. The empirical results show that the OVX changes are the dominant factor, which has a positive impact on the USDCNYV1M changes and the VXFXI changes during periods of important political and economic events. Moreover, USDCNYV1M changes are the key factor affecting the impact of OVX changes on VXFXI changes. When the oil crisis, exchange rate reform, and stock market crash occurred during 2014–2016, the positive effects of uncertainty transmission among the oil market, the Chinese stock market, and the bilateral exchange rate are significantly strengthened. Finally, we find that the positive effects are significant in the short term but diminish over time.     

The asymmetric effect of crude oil prices on stock prices in major international financial markets

The aim of this paper is to explore the potential asymmetric impacts of positive and negative shocks in crude oil prices on stock prices in six major international financial markets which include China, Hong Kong, America, Japan, Britain, and Germany. We test for these asymmetric effects on 8 major international financial markets indices over the 2007M01–2020M03 periods. Our independent measures include the prices of Brent crude oil futures and West Texas Intermediate (WTI) futures. We use the nonlinear ARDL (NARDL) model proposed by Shin et al. (2014), which can capture both short- and long-run nonlinearities through positive and negative partial sum decompositions of the explanatory variables. This research finds that positive and negative fluctuations of oil price have asymmetric effects on stock price index in four financial markets, but the performance of the asymmetry is different. Specifically, the impacts of volatility in oil prices on two indices of Chinese stock prices are different, and the asymmetric effects of oil price volatility on stock price indices in China and other financial markets are significantly different.     

The impact of oil on equity returns of Canadian and U.S. Railways and airlines

The purpose of this paper is to investigate the relationship between oil price movements and equity returns of railways and airline in Canada and the U.S. Using a robust set of oil measures, which includes both West Texas Intermediate (WTI) and Western Canadian Select (WCS) data, this research finds that railways and airlines react uniquely to oil price movements. Specifically, equity returns of railways in Canada and airlines in the U.S. tend to be negatively impacted by positive movements in WTI. Equity returns of airlines in Canada and railways in the U.S show limited evidence of any impact. Additional estimations suggest that equity returns of airlines react asymmetrically and that information regarding oil price movements may gradually diffuse over time. With the changing North American energy landscape (e.g., oil sands and shale oil), the increased reliance on transporting crude oil via railways should lead academics and practitioners to further research in this area.     

The motifs of risk transmission in multivariate time series: Application to commodity prices

In this article we propose to exploit topological information embedded in forecast error variance decomposition derived from large Bayesian vector autoregressive models (VAR) to study network connectedness and risk transmission of multivariate time series observations. Firstly, we design a robust link classification procedure based on shortest paths, so to identify salient directional spillovers in a high-dimensional framework. Secondly, we study recurrent and statistically significant sub-graphs, i.e. network motifs, on the induced network backbone by means of null models which account for local node heterogeneity. The methodology is applied to analyze spillover networks of a set of global commodity prices. We demonstrate that spillovers become key drivers of the system variance during commodity price bubbles and bursts, giving raise to complex triadic structures which do not manifest during normal business periods. By accounting for local node connectivity, we observe a departure from the null models due to the high participation of Crude Oil, Food and Beverages and Raw Materials in complex recurrent sub-graphs.     

Understanding the conditional out-of-sample predictive impact of the price of crude oil on aggregate equity return volatility

Using monthly data from 1973 through 2020, we explore whether it is possible to improve the accuracy of one-month ahead log-aggregate equity return realized volatility point forecasts by conditioning on various nonlinear crude oil price measures widely relied on in the literature. When evaluating the evidence of unconditional relative equal predictive ability as specified in Diebold and Mariano (1995), we observe that similar to well-known economic variables, such as the dividend yield, the default yield spread and the rate of inflation, we rarely observe evidence of statistical gains in relative point forecast accuracy in favor of the crude oil price-based models. However, when evaluating the evidence of conditionalrelative equal predictive ability as specified in Giacomini and White (2006), we observe that contrary to well-known economic predictors, certain nonlinear crude oil price variables, such as the one-year net crude oil price increase suggested in Hamilton (1996) offer sizable point forecast accuracy gains relative to the benchmark. These statistical gains can also be translated into economic gains.     

The impact of numerical superstition on the final digit of stock price

This paper investigates the extent to which the frequency distribution of the rightmost digit of stock prices is influenced by numerical superstitions. To identify the moderating variables that strengthen the superstition for numbers, we take into account factors including the amount of information, change of tick size, Chinese festivals, and bear market effect. Furthermore, we examine whether the frequency of lucky (unlucky) numbers as the final digit of prices decreases (increases) for firms with higher trading by institutional investors. The results indicate that investors in the Taiwan Stock Exchange tend to avoid number 4. Our results also find that the effects of numerical superstitions on the frequency of the final digit decrease when the amount of information increases. Investors appear to be more likely to avoid unlucky number 4 in the following four conditions: when the tick size becomes smaller, when it is one week before Chinese New Year, when it is the seventh month in the lunar calendar, and when it is in a bear market. We further document that institutional investors are not affected by numerical superstition. Moreover, our results support the notion that informed traders buy and sell more (less) actively the stocks with a lower (higher) frequency of prices ending with 4.     

The impact of selected factors on new business formation in the private healthcare sector

Numerous factors influence the development of the private healthcare sector. Therefore, the selection of these factors, which represent a potential opportunity for forming new entities, is a crucial from the point of view of entrepreneurship. In our research we selected strategic variables which have got direct influence on entrepreneurship in the private healthcare sector in Poland. Theoretical approach was based on literature review which have revealed the main factors and their relationships with entrepreneurship according to the previous research studies. This research study was conducted for the entire population of municipalities in Poland. Methodology was based on Intelligent Data Analysis (IDA) which can be applied for a large amounts of data in order to extract useful knowledge from it. Moreover, in research study were applied explanation techniques – decision rules –in order to indicate, to what extent the environment have influence on strategic choices conditioning the success of businesses. The results have revealed that it is possible to determine a set of the most important factors influencing entrepreneurship in the private healthcare sector in Poland. On the other hand, were indicated these variables which do not participate in process of influencing on entrepreneurship in private healthcare sector in Poland.

     

The effects of foreign exchange and monetary policies in Russia

This paper examines the effects of Russian foreign exchange and monetary policies under conditions of abundant natural resources during the period 1999–2011 using structural VAR models. The results suggest that monetary policy shocks, which are identified as money supply disturbances, have a persistent effect on real output, and more than half of the volatility in real output can be explained by changes in the money supply. Furthermore, the analysis reveals that stock prices are a more significant transmission channel of monetary policy than bank loans.     

The impact of the macroeconomic factors in the bank efficiency: Evidence from the Chinese city banks

This study uses stochastic frontier analysis to examine the impact of the regional disparities in the cost and profit efficiency for a sample of city commercial banks in China from 2005 to 2014. The results indicate that bank efficiency of Chinese City Commercial banks is positively correlated to the per capital GDP but negatively linked to urban population ratio. However, compared the eastern and non-eastern regions, there is a significant difference in effects of macroeconomic factors for bank efficiency. The macroeconomic conditions influence the efficiency of Chinese City Commercial banks in eastern regions are more significant than the others.     

The impact of the logistics service standardization on firm value: Evidence from China

In 2014, the Standardization Administration of China launched its first pilot project of the logistics service standardization (LSS). We examine whether the staggered adoption of the LSS creates value for shareholders using a difference-in-difference research design. The findings suggest that firms located in LSS cities have higher firm value in terms of Tobin’s Q and stock returns than those of non-LSS cities. In further analysis, we find that the LSS enhances firm value by improving corporate operational efficiency. However, the LSS increases large firms’ market share at the expense of small firms. Overall, our findings advance the literature of logistics system reform and show that such reform creates value for shareholders.     

The impact of individual and institutional investor sentiment on the market price of risk

We examine the effect of individual and institutional investor sentiment on the market price of risk derived from DJIA and S&P500 index returns. Consistent with behavioral asset pricing models, we find significant positive response of rational sentiment suggesting greater incentive for rational investors to engage in arbitrage when the compensation for taking risk is greater. Further, an increase in irrational optimism leads to a significant downward movement, but an increase in rational sentiment does not lead to a significant change market price of risk. These results are robust for both market indexes, DJIA and S&P500 and for both individual and institutional investor sentiment.     

The impact of patents and standards on macroeconomic growth: a panel approach covering four countries and 12 sectors

Based on the assumption that codified technological know-how contributes to economic growth, this paper presents the estimation of a Cobb–Douglas production function, pooling data from four European countries and 12 sectors. The empirical results confirm that both the stock of patents and the stock of technical standards contribute significantly to economic growth in the 1990s. Whereas the results of the country models are rather similar, we observe significant differences between the sector models, which indicate that standards are more important for growth in less R&D-intensive industries and patents in R&D-intensive industries.