Matteo Manera

Econometric Models of Asymmetric Price Transmission

In this paper we review the existing empirical literature on price asymmetries in commodities, providing a way to classify and compare different studies which are highly heterogeneous in terms of econometric models, type of asymmetries and empirical findings. Relative to the previous literature, this paper is novel in several respects. First, it presents a detailed and updated survey of the existing empirical contributions on the existence of price asymmetries in the transmission mechanism linking input prices to output prices. Second, this paper presents an extension of the traditional distinction between long-run and short-run asymmetries to new categories of asymmetries, such as: contemporaneous impact, distributed lag effect, cumulated impact, reaction time, equilibrium and momentum equilibrium adjustment path, regime effect, regime equilibrium adjustment path. Third, each empirical study is critically discussed in the light of this new classification of asymmetries. Fourth, this paper evaluates the relative merits of the most popular econometric models for price asymmetries, namely autoregressive distributed lags, partial adjustments, error correction models, regime switching and vector autoregressive models.

Rockets and Feathers Revisited: an International Comparison on European Gasoline Markets

This paper re-examines the issue of asymmetries in the transmission of shocks to crude oil prices onto the retail price of gasoline. Relative to the previous literature, the distinguishing features of the present paper are - i) use of updated and comparable data to carry out an international comparison of gasoline markets; ii) two-stage modeling of the transmission of oil price shocks to gasoline prices (first refinery stage and second distribution stage), in order to assess possible asymmetries at either one or both stages; iii) use of asymmetric error correction models to distinguish between asymmetries that arise from short-run deviations in input prices and from the speed at which the gasoline price reverts to its long-run level; iv) explicit, possibly asymmetric, role of the exchange rate, as crude oil is paid for in dollars whereas gasoline sells for different sums of national currencies; v) bootstrapping of F tests of asymmetries, in order to overcome the lowpower problem of conventional testing procedures. In contrast to several previous findings, the results generally point to widespread differences in both adjustment speeds and short-run responses when input prices rise or fall.

On the Robustness of Robustness Checks of the Environmental Kuznets Curve

Since its first inception in the debate on the relationship between environment and growth in 1992, the Environmental Kuznets Curve has been subject of continuous and intense scrutiny. The literature can be roughly divided in two historical phases. Initially, after the seminal contributions, additional work aimed to extend the investigation to new pollutants and to verify the existence of an inverted-U shape as well as assessing the value of the turning point. The following phase focused instead on the robustness of the empirical relationship, particularly with respect to the omission of relevant explanatory variables other than GDP, alternative datasets, functional forms, and grouping of the countries examined. The most recent line of investigation criticizes the Environmental Kuznets Curve on more fundamental grounds, in that it stresses the lack of sufficient statistical testing of the empirical relationship and questions the very existence of the notion of Environmental Kuznets Curve. Attention is in particular drawn on the stationarity properties of the series involved – per capita emissions or concentrations and per capita GDP – and, in case of presence of unit roots, on the cointegration property that must be present for the Environmental Kuznets Curve to be a well-defined concept. Only at that point can the researcher ask whether the long-run relationship exhibits an inverted-U pattern. On the basis of panel integration and cointegration tests for sulphur, Stern (2002, 2003) and Perman and Stern (1999, 2003) have presented evidence and forcefully stated that the Environmental Kuznets Curve does not exist. In this paper we ask whether similar strong conclusions can be arrived at when carrying out tests of fractional panel integration and cointegration. As an example we use the controversial case of carbon dioxide emissions. The results show that more EKCs come back into life relative to traditional integration/cointegration tests. However, we confirm that the EKC remains a fragile concept.

Modelling time-varying conditional correlations in the volatility of Tapis oil spot and forward returns

This paper estimates the dynamic conditional correlations in the returns on Tapis oil spot and one-month forward prices for the period 2 June 1992 to 16 January 2004, using recently developed multivariate conditional volatility models, namely the Constant Conditional Correlation Multivariate GARCH (CCC–MGARCH) model of Bollerslev (1990), Vector Autoregressive Moving Average–GARCH (VARMA–GARCH) model of Ling and McAleer (2003), VARMA–Asymmetric GARCH (VARMA–AGARCH) model of Hoti et al. (2002), and the Dynamic Conditional Correlation (DCC) model of Engle (2002). The dynamic correlations are extremely useful in determining whether the spot and forward returns are substitutes or complements, which can be used to hedge against contingencies. Both the univariate ARCH and GARCH estimates are significant for spot and forward returns, whereas the estimates of the asymmetric effect at the univariate level are not statistically significant for either spot or forward returns. Standard diagnostic tests show that the AR(1)–GARCH(1, 1) and AR(1)–GJR(1, 1) specifications are statistically adequate for both the conditional mean and the conditional variance. The multivariate estimates for the VAR(1)–GARCH(1, 1) and VAR(1)–AGARCH(1, 1) models show that the ARCH and GARCH effects for spot (forward) returns are significant in the conditional volatility model for spot (forward) returns. Moreover, there are significant interdependences in the conditional volatilities between the spot and forward markets. The multivariate asymmetric effects are significant for both spot and forward returns. Overall the multivariate VAR(1)–AGARCH(1, 1) dominates its symmetric counterpart. The calculated constant conditional correlations between the conditional volatilities of spot and forward returns using CCC–GARCH(1, 1), VAR(1)–GARCH(1, 1) and VAR(1)–AGARCH(1, 1) are very close to 0.93. Virtually identical results are obtained when the three constant conditional correlation models are extended to include two lags in both the ARCH and GARCH components. Finally, the estimates of the two DCC parameters are statistically significant, which makes it clear that the assumption of constant conditional correlation is not supported empirically. This is highlighted by the dynamic conditional correlations between spot and forward returns, for which its sample mean is virtually identical to the computed constant conditional correlation, regardless of whether a DCC–GARCH(1, 1) or a DCC–GARCH(2, 2) is used. For these models, the dynamic conditional correlations are in the range (0.417, 0.993) and (0.446, 0.993), signifying medium to extreme interdependence. Therefore, the dynamic volatilities in the returns in Tapis oil spot and forward markets are generally interdependent over time. These findings suggest that a sensible hedging strategy would consider spot and forward markets as being characterized by different degrees of substitutability.

Financial Speculation in Energy and Agriculture Futures Markets: A Multivariate GARCH Approach

This paper analyses futures prices of four energy commodities (crude oil, heating oil, gasoline and natural gas) and five agricultural commodities (corn, oats, soybean oil, soybeans and wheat), over the period 1986-2010. Using DCC multivariate GARCH models, it provides new evidence on four research questions: 1) Are macroeconomic factors relevant in explaining returns of energy and non-energy commodities? 2) Is financial speculation significantly related to returns in futures markets? 3) Are there significant relationships among returns, either in their mean or variance, across different markets? 4) Is speculation in one market affecting returns in other markets? Results suggest that the SP G13; Q11; Q43.

Returns in Commodities Futures Markets and Financial Speculation: A Multivariate GARCH Approach

This paper analyses futures prices for four energy commodities (light sweet crude oil, heating oil, gasoline and natural gas) and five agricultural commodities (corn, oats, soybean oil, soybeans and wheat), over the period 1986-2010. Using CCC and DCC multivariate GARCH models, we find that financial speculation is poorly significant in modelling returns in commodities futures while macroeconomic factors help explaining returns in commodities futures. Moreover, spillovers between commodities are present and the conditional correlations among commodities are high and time-varying.

The Health Effects of Climate Change: A Survey of Recent Quantitative Research

In recent years there has been a large scientific and public debate on climate change and its direct as well as indirect effects on human health. In particular, a large amount of research on the effects of climate changes on human health has addressed two fundamental questions. First, can historical data be of some help in revealing how short-run or long-run climate variations affect the occurrence of infectious diseases? Second, is it possible to build more accurate quantitative models which are capable of predicting the future effects of different climate conditions on the transmissibility of particularly dangerous infectious diseases? The primary goal of this paper is to review the most relevant contributions which have directly tackled those questions, both with respect to the effects of climate changes on the diffusion of non-infectious and infectious diseases, with malaria as a case study. Specific attention will be drawn on the methodological aspects of each study, which will be classified according to the type of quantitative model considered, namely time series models, panel data and spatial models, and non-statistical approaches. Since many different disciplines and approaches are involved, a broader view is necessary in order to provide a better understanding of the interactions between climate and health. In this respect, our paper also presents a critical summary of the recent literature related to more general aspects of the impacts of climate changes on human health, such as: the economics of climate change; how to manage the health effects of climate change; the establishment of Early Warning Systems for infectious diseases.

On the Economic Determinants of Oil Production - Theoretical Analysis and Empirical Evidence for Small Exporting Countries

In this paper, decisions regarding production in oil exporting countries are studied by means of theoretical analysis and empirical investigation. Under the assumptions of exogenous oil prices and world oil demand, we are able to describe the relationship between oil production levels and changes in the conditions in world oil markets. Intertemporal production decisions by a representative oil producer are modelled by means of a partial equilibrium model. In this theoretical model, oil producers are subject to exogenous shocks in world oil demand and prices. Oil companies can change output levels only by incurring a fixed cost. Results from the simulation of this model show a strong relationship between oil production and changes in world oil consumption. On the contrary, the effects of changes in real oil prices on oil production decisions seem to be much lower. Results from the simulation of the theoretical model are then empirically investigated using time-series econometric techniques. The empirical evidence supports the hypothesis that several oil producing countries are characterized by different responses to changes in world oil demand and in real oil prices. For many countries production rapidly adjusts to changes in consumption whereas responses of oil production to innovations in real oil prices are found to be not statistically significant. In addition, when non-linearities in the relationship between exogenous variables and output levels are allowed for, evidence of asymmetric effects of output levels to shocks in demand levels and oil prices is found.

Biofuels and Food Prices: Searching for the Causal Link

We analyze the relationship between the prices of ethanol, agricultural commodities and livestock in Nebraska, the U.S. second largest ethanol producer. The paper focuses on long-run relations and Granger causality linkages between ethanol and the other commodities. The analysis takes possible structural breaks into account and uses a set of techniques that allow to draw inferences about the existence of long-run relations and of short-run in-sample Granger causality and out-ofsample predictive ability. Even after taking breaks into account, evidence that the price of ethanol drives the price dynamics of the other commodities is extremely weak. It is concluded that, on the basis of a formal, comprehensive and rigorous causality analysis we do not find evidence in favour of the Food versus Fuel debate.

Modelling electricity prices: from the state of the art to a draft of a new proposal

In the last decades a liberalization of the electric market has started; prices are now determined on the basis of contracts on regular markets and their behaviour is mainly driven by usual supply and demand forces. A large body of literature has been developed in order to analyze and forecast their evolution: it includes works with different aims and methodologies depending on the temporal horizon being studied. In this survey we depict the actual state of the art focusing only on the recent papers oriented to the determination of trends in electricity spot prices and to the forecast of these prices in the short run. Structural methods of analysis, which result appropriate for the determination of forward and future values are left behind. Studies have been divided into three broad classes: Autoregressive models, Regime switching models, Volatility models. Six fundamental points arise: the peculiarities of electricity market, the complex statistical properties of prices, the lack of economic foundations of statistical models used for price analysis, the primacy of uniequational approaches, the crucial role played by demand and supply in prices determination, the lack of clearcut evidence in favour of a specific framework of analysis. To take into account the previous stylized issues, we propose the adoption of a methodological framework not yet used to model and forecast electricity prices: a time varying parameters Dynamic Factor Model (DFM). Such an eclectic approach, introduced in the late ‘70s for macroeconomic analysis, enables the identification of the unobservable dynamics of demand and supply driving electricity prices, the coexistence of short term and long term determinants, the creation of forecasts on future trends. Moreover, we have the possibility of simulating the impact that mismatches between demand and supply have over the price variable. This way it is possible to evaluate whether congestions in the network (eventually leading black out phenomena) trigger price reactions that can be considered as warning mechanisms.