Oil price shocks and economic growth: The volatility link

This paper shows that oil shocks impact economic growth primarily through the conditional variance of growth. Our comparison of models focuses on density forecasts. Over a range of dynamic models, oil shock measures and data, we find a robust link between oil shocks and the volatility of economic growth. We then develop a new measure of oil shocks and show that it is superior to existing measures; it indicates that the conditional variance of growth increases in response to an indicator of the local maximum oil price exceedance. The empirical results uncover a large pronounced asymmetric response of the growth volatility to oil price changes. The uncertainty about future growth is considerably lower than with a benchmark AR(1) model when no oil shocks are present.     

The response of prices,sales, and output to temporary changes in demand

We determine empirically how automakers accommodate shocks to demand. Using data on production, sales, and transaction prices, we estimate a dynamic profit maximization model of the firm. We demonstrate that when an automaker is hit with a vehicle‐specific demand shock, sales respond immediately and prices respond very modestly. Further, when accounting for non‐convexities in the cost function, production responds with a delay. Over time, shocks are absorbed almost entirely through adjustments in sales and production rather than prices. We examine two recent demand shocks: the Ford Explorer/Firestone tire recall of 2000, and the 11 September 2001 terrorist attacks. Copyright © 2009 John Wiley & Sons, Ltd.     

What׳s news in News? A cautionary note on using a variance decomposition to assess the quantitative importance of news shocks

This paper points out a conceptual difficulty in using a variance decomposition to assess the quantitative importance of news shocks. A variance decomposition will attribute to news shocks movements in endogenous variables driven both by news about future exogenous fundamentals that has yet to materialize (what I call “pure news”) as well as movements driven by realized changes in fundamentals that were anticipated in the past (what I call “realized news”). I present a stylized model in which news about yet unrealized changes in fundamentals is irrelevant for output dynamics, but in which a variance decomposition may nevertheless attribute a large share of the variance of output to news shocks. I then revisit the quantitative importance of news in the model of Schmitt-Grohe and Uribe (2012). In their model news shocks account for 40 percent of the variance of output growth, but this is mostly driven by realized news.     

Refining Stylized Facts from Factor Models of Inflation

Factor models of disaggregate inflation indices suggest that sectoral shocks generate the bulk of sectoral inflation variance, but no persistence. Aggregate shocks, by contrast, are the root of sectoral inflation persistence, but have negligible relative variance. We show that simple factor models do not cope well with essential features of price data. In particular, sectoral inflation series are subject to features such as measurement error, sales and item substitutions. In factor models, these blow up the variance of sector‐specific shocks, while reducing their persistence. We control for such effects by estimating a refined factor model and find that inflation variance is driven by both aggregate and sectoral shocks. Sectoral shocks, too, generate substantial inflation persistence. Both findings contrast with earlier evidence from factor models, but align well with recent micro evidence. Our results have implications for the foundations of price stickiness, and provide quantitative inputs for calibrating models with sectoral heterogeneity. Copyright © 2014 John Wiley & Sons, Ltd.     

What inventories tell us about aggregate fluctuations—A tractable approach to (S,s) policies

We estimate a DSGE model with (S,s) inventory policies. We find that (i) taking inventories into account can significantly improve the empirical fit of DSGE models in matching the standard business-cycle moments (in addition to explaining inventory fluctuations); (ii) (S,s) inventory policies can significantly amplify aggregate output fluctuations, in contrast to the findings of the recent general-equilibrium inventory literature; and (iii) aggregate demand shocks become more important than technology shocks in explaining the business cycle once inventories are incorporated into the model. An independent contribution of our paper is that we develop a solution method for analytically solving (S,s) inventory policies in general equilibrium models with heterogeneous firms and a large aggregate state space, and we illustrate how standard log-linearization methods can be used to solve various versions of our inventory model, generate impulse response functions, and estimate the model׳s deep structural parameters.     

Do U.S. macroeconomic surprises influence equity returns? An exploratory analysis of developed economies

Given the dominant role the U.S. economy plays in global trade, we explore how U.S. macroeconomic surprises affect stock markets in ten major developed economies as well as in China and India. We do not find strong enough evidence to conclude that U.S. macro shocks materially and consistently influence equity returns and volatilities in the economies studied. Consistent with previous research, it appears that only in few markets are return levels materially influenced by macro surprises generated in the U.S. Also, only a small number of macro shocks seem to be of any consistent significance. For returns levels, inflation, productivity, consumer confidence, and retail sales seem to matter. At the same time, conditional volatilities appear to be influenced by inflation, retail sales, durable goods, industrial production, consumer confidence, gross domestic product, and trade balance surprises. Finally, our exploratory analysis indicates that the degree of bilateral trade connectedness may partially explain the extent to which macroeconomic surprises are transmitted across countries.     

List price and sales prices of residential properties during booms and busts

This paper investigates the relationship between the list and sale price of residential properties over the housing cycle. In down or normal markets the list price generally exceeds the sales price; however, when the housing market is strong, homes sell for more than their list price. This observation is not consistent with the assumptions made in the standard model of home sellers’ search behavior. We consider alternative models. In one, sellers set list prices based on their expectations of future changes in sales prices and the arrival rate of buyers; however, demand shocks occur. This model partially explains our data from the Belfast, U.K. housing market, but it fails to predict the list to sales price ratio during a sustained housing boom. We next describe a model where sellers’ endogenously select their search mechanism depending on the strength of the housing market. We find support for the conjecture that sellers switch to an auction-like model during housing booms. There also is evidence that during a downturn in the market, sellers’ list prices are sticky.     

随机需求下销售周期对零售商绩效影响的仿真分析

运用系统动力学方法构建了包含市场需求、企业生产、劳动力和库存管理的一级供应链运作模型。通过灵敏度和优化分析仿真技术研究了随机需求下产品销售周期对零售商成本、利润和供应链牛鞭效应的影响。结论显示,与生产成本和劳动力成本相比,库存成本对产品销售周期的变化更敏感;在不考虑生产启动成本情况下,随着销售周期增大,总利润呈线性递减;连续库存补充计划比传统的经济订货批量模式能够为企业带来更多的利润,更有利于减弱牛鞭效应的影响。     

Wars and capital destruction

In this paper, we propose a theoretical framework to investigate the impact of conflicts and wars on key macroeconomic aggregates and welfare. Using a panel data with 9 countries from 1870 onwards, we first show that the consumption-to-output ratio is minimal during WWII for participants. While this can be explained by an increase in public spending in the USA, this cannot be the case in other countries that participated in WWII, as they experience a large fall in output during wartime. To account for this, we build a variation of a Real Business Cycle model first proposed by Hercowitz and Sampson (1991). We extend the initial model to account for specific shocks that destroy private and public capital stocks – as conflicts do – by assuming an (exogenously) time-varying parameter in the law of capital accumulation. In addition, the model imbeds generalized TFP shocks capturing standard technological factors as well as the potential effects of war on the labor force. The model is estimated and used (i) to assess the importance of capital shocks during war episodes, and (ii) to quantify the welfare effects of conflicts. We show that capital shocks are crucial to account for the macroeconomic dynamics of countries that have experienced large war-related destruction, and that the welfare losses from fluctuations can be quite large when considering data samples that include major war episodes.     

The impacts of investor sentiment on returns and conditional volatility of international stock markets

One of the main arguments of behavioral finance is that some properties of asset prices are most probably regarded as deviations from fundamental value and they are generated by the participation of traders who are not fully rational, thus called noise traders. Noise trader theory postulates that sentiment traders have greater impact during high-sentiment periods than during low-sentiment periods, and sentiment traders miscalculate the variance of returns undermining the mean-variance relation. The main objective of this research is to construct a model to evaluate the returns and conditional volatility of various stock market indexes considering the changes in the investor sentiment by measuring the effects of noise trader demand shocks on returns and volatility. EGARCH model is used to determine whether earning shocks have more influence on the conditional volatility in high sentiment periods weakening the mean–variance relation. This paper takes an international approach using weekly market index returns of U.S., Japan, Hong Kong, U.K., France, Germany, and Turkey. Weekly trading volumes of these indexes are regressed against a group of macroeconomic variables and the residuals are used as proxies for investor sentiment and significant evidence is found that there is asymmetric volatility in these market indexes and earning shocks have more influence on conditional volatility when the sentiment is high.     

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.     

Asset prices with non-permanent shocks to consumption

Most standard asset-pricing models assume that all shocks to consumption are permanent. We relax this assumption and allow also for non-permanent shocks. In our specification, the long-run mean of consumption growth is constant; consumption levels are subject to short-run deviations from their long-run trend. The implications of our model are dramatically different from those obtained in the prior literature. A canonical and parsimonious asset pricing model with CRRA preferences and non-permanent shocks can reproduce the equity premium, high return volatility and return predictability with a coefficient of relative risk aversion below ten. This finding suggests that non-permanent shocks can play an important role in explaining asset pricing puzzles.     

Financial intermediation and real estate prices impact on business cycles: A Bayesian analysis

How do financial intermediation and real estate prices impinge on the business cycle? I develop a two-sector stochastic general equilibrium model with financial intermediation and real estate collateral to assess the impact of financial conditions and land prices on aggregate fluctuations. I estimate the model with Bayesian methods using a novel data set that includes U.S. macro and financial variables during the period 1975–2010. The results from the estimated model show that financial conditions have a sizable effect on the variability of investment spending, while productivity shocks are the main source of consumption fluctuations. Specifically, on the macro side, (1) financial shocks explain about three quarters of investment spending variability and one third of the variance in hours worked. On the financial side, (2) financial shocks explain most of the variability in land prices, credit spread, and aggregate net worth of the financial sector. The model also accounts for observed unconditional moments of macro and financial variables. Our quantitative results are suggestive of the impact of diverse sources of financial instability, and as such relevant for macro prudential policy analysis.     

Growth and real business cycles in Vietnam and the Asean-5. Does the trend shock matter?

We examine Vietnam’s economy in comparison with its closest trade partners. We show that capital accumulation has been the primary growth engine since the start of its transition to the pro-market economy in 1986 – the Doi Moi. We also show that the cyclical behavior of its macro aggregates is similar to that of its ASEAN-5 peers and other developing countries. We extend the standard small open economy RBC model by considering habit persistence and government consumption, which allows a close match of the moments of the growth variables. At the business cycle frequency, transitory productivity shocks account for approximately one-half of Vietnam’s output variance, while country risk and non-transitory productivity shocks account to close to one-fifth each. Regarding the Solow residual’s volatility, we find that the trend component merely accounts for 12 % of this variance in Vietnam, while in Thailand it is only 6 %. These findings refute the “the cycle is the trend” hypothesis in Aguiar and Gopinath (2007) and align with the hypotheses in García-Cicco et al. (2010) and Rhee (2017), where the stationary component is overwhelmingly dominant. We claim that technological progress and productivity-enhancing measures are fundamental for Vietnam’s economy to sustain high growth.     

Threshold arch models and asymmetries in volatility

This paper attempts to enlarge the class of Threshold Heteroscedastic Models (TARCH) introduced by Zakoían (1991a). We show that it is possible to relax the positivity constraints on the parameters of the conditional variance. Unconstrained models provide a greater generality of the paths allowing for nonlinearities in the volatility. Cyclical behaviour is permitted as well as different relative impacts of positive and negative shocks on volatility, depending on their size. We give empirical evidence using French stock returns.     

Economic impact of enhanced forest inventory information and merchandizing yards in the forest product industry supply chain

Forest products industry should maximize the value of timber harvested and associated products in order to be competitive in global markets. Enhanced forest inventories and merchandizing yards can help in maximizing value recovery in the forest products supply chain. This study develops an optimization model to analyze the economic impact of enhanced forest inventory information and merchandizing yard operations in the forest products supply chain. The application of the model is demonstrated by using a case study of a hypothetical forest industry in northwestern Ontario, which obtains four log assortment grades from the surrounding eight forest management units. The model analyzes five different scenarios with 0%, 25%, 50%, 75%, and 100% certainty of tree quality in forest inventory information. The results of the study show that with full certainty of tree quality information, it is possible to gain 49% in gross profit in comparison with a scenario with no certainty. The usefulness of enhanced forest inventory and merchandizing yard in the entire supply chain of forest products industry is recognized by maximizing total value of wood fiber (by allocating right log to the right product), reducing fluctuations in raw wood fiber supply, and minimizing inventory carrying costs and lost sales.     

On the interpretation of cointegration in the linear–quadratic inventory model

The traditional formulation of the linear–quadratic inventory model with unit roots predicts cointegration between inventories and sales. That formulation implies that marginal production costs and the marginal benefits of inventories are both tending to ∞, and the cointegrating coefficient reflects the optimal trade-off between these competing factors. This paper suggests a reformulation of the problem in which marginal production costs and marginal inventory benefits are both stationary and in which the cointegrating coefficient is the same as the value that characterizes the target inventory level in the cost function.     

SALES,INVENTORIES AND REAL INTEREST RATES: A CENTURY OF STYLIZED FACTS

We use Bayesian time‐varying parameter structural vector autoregressions with stochastic volatility to investigate changes in reduced‐form and structural correlations between inventories and either sales growth or the real interest rate in the USA during both the inter‐war and post‐World War II periods. We identify four structural shocks by combining a single long‐run restriction to identify a permanent output shock with three sign restrictions to identify demand‐ and supply‐side transitory shocks. We show that during both the inter‐war and post‐war periods the structural correlation between inventories and real interest rate conditional on identified interest rate shocks is systematically positive; the reduced‐form correlation between the two series is positive during the post‐war period, but in line with the predictions of theory it is robustly negative during the inter‐war era; during that era the correlations between inventories and either of the two other series exhibit a remarkably strong co‐movement with output at business cycle frequencies. Copyright © 2014 John Wiley & Sons, Ltd.     

THE RESURGENCE OF INVENTORY RESEARCH: WHAT HAVE WE LEARNED?

Abstract. Recent empirical and theoretical research on business inventories is surveyed and critically evaluated. While most inventory research has had macroeconomic motivations, we focus on its microtheoretic basis and on potential conflicts between theory and evidence. The paper asks two principal questions. First, how can inventories, which are allegedly used by firms to stabilize production, nonetheless be a destabilizing factor at the macroeconomic level? Second, why, if firms are following the production-smoothing model, is production more variable than sales in many industries? We suggest that the so-called (S,s) model may help answer both questions.     

存货购销中最优期权合约交易量研究

在分析利用期权合约规避价格波动风险的原理的基础上,分别给出存货购销两个环节中可以运用的期权策略,然后利用均值方差模型计算使投资组合达到效用最大化时所对应的最优期权合约交易量及其对经营利润的影响,研究发现：在存货采购环节,企业可以通过购入看涨期权、购入看涨期权同时售出看跌期权两种策略控制采购价格波动的风险,在存货销售环节,企业可以通过购入看跌期权、同时购入看跌期权并售出看涨期权两种策略来稳定销售利润;从最优期权合约交易量及其对企业经营利润的影响来看,期权工具在控制存货采购价格、稳定销售利润中可以发挥良好作用。