Preferences, common knowledge and speculative trade

We study the proposition that if it is common knowledge that en allocation of assets is ex-ante pareto efficient, there is no further trade generated by new information. The key to this result is that the information partitions and other characteristics of the agents must be common knowledge and that contracts, or asset markets, must be complete. It does not depend on learning, on 'lemons' problems, nor on agreement regarding beliefs and the interpretation of information. The only requirement on preferences is state-additivity; in particular, traders need not be risk-averse. We also prove the converse result that "no-trade results" imply that traders' preferences can be represented by state-additive utility functions. We analyze why examples of other widely studied preferences (e.g., Schmeidler (1989)) allow "speculative" trade.

Common agency with informed principals

We analyze a common agency game under asymmetric information on the preferences of the non-cooperating principals in a public good context. Asymmetric information introduces incentive compatibility constraints which rationalize the requirement of truthfulness made in the earlier literature on common agency games under complete information. There exists a large class of differentiable equilibria which are ex post inefficient and exhibit free-riding. We then characterize some interim efficient equilibria. Finally, there exists also a unique equilibrium allocation which is robust to random perturbations. This focal equilibrium is characterized for any distribution of types.

Estimating sectoral cycles using cointegration and common features

This paper investigates the degree of short run and long run co-movement in U.S. sectoral output data by estimating sectoraI trends and cycles. A theoretical model based on Long and Plosser (1983) is used to derive a reduced form for sectoral output from first principles. Cointegration and common features (cycles) tests are performed; sectoral output data seem to share a relatively high number of common trends and a relatively low number of common cycles. A special trend-cycle decomposition of the data set is performed and the results indicate a very similar cyclical behavior across sectors and a very different behavior for trends. Indeed. sectors cyclical components appear as one. In a variance decomposition analysis, prominent sectors such as Manufacturing and Wholesale/Retail Trade exhibit relatively important transitory shocks.

Common cycles in macroeconomic aggregates (revised version)

Although there has been substantial research on long-run co-movement (common trends) in the empirical macroeconomics literature. little or no work has been done on short run co-movement (common cycles). Investigating common cycles is important on two grounds: first. their existence is an implication of most dynamic macroeconomic models. Second. they impose important restrictions on dynamic systems. Which can be used for efficient estimation and forecasting. In this paper. using a methodology that takes into account short- and long-run co-movement restrictions. we investigate their existence in a multivariate data set containing U.S. per-capita output. consumption. and investment. As predicted by theory. the data have common trends and common cycles. Based on the results of a post-sample forecasting comparison between restricted and unrestricted systems. we show that a non-trivial loss of efficiency results when common cycles are ignored. If permanent shocks are associated with changes in productivity. the latter fails to be an important source of variation for output and investment contradicting simple aggregate dynamic models. Nevertheless. these shocks play a very important role in explaining the variation of consumption. Showing evidence of smoothing. Furthermore. it seems that permanent shocks to output play a much more important role in explaining unemployment fluctuations than previously thought.

Common cycles in macroeconomic aggregates

Reduced form estimation of multivariate data sets currently takes into account long-run co-movement restrictions by using Vector Error Correction Models (VECM' s). However, short-run co-movement restrictions are completely ignored. This paper proposes a way of taking into account short-and long-run co-movement restrictions in multivariate data sets, leading to efficient estimation of VECM' s. It enables a more precise trend-cycle decomposition of the data which imposes no untested restrictions to recover these two components. The proposed methodology is applied to a multivariate data set containing U.S. per-capita output, consumption and investment Based on the results of a post-sample forecasting comparison between restricted and unrestricted VECM' s, we show that a non-trivial loss of efficiency results whenever short-run co-movement restrictions are ignored. While permanent shocks to consumption still play a very important role in explaining consumption’s variation, it seems that the improved estimates of trends and cycles of output, consumption, and investment show evidence of a more important role for transitory shocks than previously suspected. Furthermore, contrary to previous evidence, it seems that permanent shocks to output play a much more important role in explaining unemployment fluctuations.

Common currency and economic integration in Mercosur

A América Latina tem uma longa história de tentativas de alcançar uma integração regional, embora seu sucesso tenha sido modesto. Este trabalho procura mostrar que isso essencialmente ocorre não tanto pelas práticas protecionistas nos vários países, mas devido à falta de uma moeda comum, ou, pelo menos, de uma taxa de câmbio rigorosamente administrada. Os autores analisaram o critério da área ótima de moeda que mostra ser prudente aumentar a integração econômica antes de tentar implementar a coordenação das taxas de câmbio. Entretanto, nós mostramos que no Mercosul já existem as condições mínimas para começar a trabalhar nessa direção. A diminuição da instabilidade cambial pode encorajar a entrada de investimentos e o comércio nas economias latino-americanas. Os autores também desenvolveram um exercício simplificado para entender como poderia ser viável alcançar estabilidade da taxa de câmbio em nos dois maiores países da região (Brasil e Argentina) e avançar na adoção de uma moeda comum.

On common agency with informed principals

This thesis consists of three chapters that have as unifying subject the frame-work of common agency with informed principals. The first two chapters analyze the economic effects of privately informed lobbying applied to tariff protection (Chapter 1) and to customs unions agreements (Chapter 2). The third chapter investigates the choice of retailing strutures when principals (the producers) are privately informed about their production costs. Chapter 1 analyzes how lobbying affects economic policy when the interest groups have private information. I assume that the competitiveness of producers are lobbies private information in a Grossman and Helpman (1994) lobby game. This allows us to analyze the e¤ects of information transmission within their model. I show that the information transmission generates two informational asymmetry problems in the political game. One refers to the cost of signaling the lobby's competitiveness to the policy maker and the other to the cost of screening the rival lobby's competitiveness from the policy maker. As an important consequence information transmission may improve welfare through the reduction of harmful lobbying activity. Chapter 2 uses the framework of chapter 1 to study a customs union agreement when governments are subject to the pressure of special interest groups that have better information about the competitiveness of the industries they represent. I focus on the agreement's effect on the structure of political influence. When join a customs union, the structure of political pressure changes and with privately informed lobbies, a new effect emerges: the governments can use the information they learn from the lobby of one country to extract rents from the lobbies of the other country. I call this the "information transmission effect". This effect enhances the governments'bargaining power in a customs union and makes lobbies demand less protection. Thus, I find that information transmission increases the welfare of the agreement and decreases tari¤s towards non-members. I also investigate the incentives for the creation of a customs union and find that information transmission makes such agreement more likely to be politically sustainable. Chapter 3 investigates the choice of retailing structure when the manufacturers are privately informed about their production costs. Two retailing structures are analyzed, one where each manufacturer chooses her own retailer (exclusive dealing) and another where the manufacturers choose the same retailer (common agency). It is shown that common agency mitigates downstream competition but gives the retailer bargaining power to extract informational rents from the manufacturers, while in exclusive dealing there is no downstream coordination but also there are no incentives problem in the contract between manufacture and retailer. A pre- liminary characterization of the choice of the retailing structure for the case of substitute goods shows that when the uncertainty about the cost increases relatively to the size of the market, exclusive dealing tends to be the chosen retailing structure. On the other hand, when the market is big relatively to the costs, common agency emerges as the retailing structure. This thesis has greatly benefited from the contribution of Professors Humberto Moreira and Thierry Verdier. It also benefited from the stimulating environment of the Toulouse School of Economics, where part of this work was developed during the year of 2007.

The importance of common cyclical features in VAR analysis: a Monte-Carlo study

Despite the commonly held belief that aggregate data display short-run comovement, there has been little discussion about the econometric consequences of this feature of the data. We use exhaustive Monte-Carlo simulations to investigate the importance of restrictions implied by common-cyclical features for estimates and forecasts based on vector autoregressive models. First, we show that the ìbestî empirical model developed without common cycle restrictions need not nest the ìbestî model developed with those restrictions. This is due to possible differences in the lag-lengths chosen by model selection criteria for the two alternative models. Second, we show that the costs of ignoring common cyclical features in vector autoregressive modelling can be high, both in terms of forecast accuracy and efficient estimation of variance decomposition coefficients. Third, we find that the Hannan-Quinn criterion performs best among model selection criteria in simultaneously selecting the lag-length and rank of vector autoregressions.

The importance of Common-Cyclical Features in VAR analysis: a Monte-Carlo study (Preliminary Version)

Despite the belief, supported byrecentapplied research, thataggregate datadisplay short-run comovement, there has been little discussion about the econometric consequences ofthese data “features.” W e use exhaustive M onte-Carlo simulations toinvestigate theimportance ofrestrictions implied by common-cyclicalfeatures for estimates and forecasts based on vectorautoregressive and errorcorrection models. First, weshowthatthe“best” empiricalmodeldevelopedwithoutcommoncycles restrictions neednotnestthe“best” modeldevelopedwiththoserestrictions, duetothe use ofinformation criteria forchoosingthe lagorderofthe twoalternative models. Second, weshowthatthecosts ofignoringcommon-cyclicalfeatures inV A R analysis may be high in terms offorecastingaccuracy and e¢ciency ofestimates ofvariance decomposition coe¢cients. A lthough these costs are more pronounced when the lag orderofV A R modelsareknown, theyarealsonon-trivialwhenitis selectedusingthe conventionaltoolsavailabletoappliedresearchers. T hird, we…ndthatifthedatahave common-cyclicalfeatures andtheresearcherwants touseaninformationcriterium to selectthelaglength, theH annan-Q uinn criterium is themostappropriate, sincethe A kaike and theSchwarz criteriahave atendency toover- and under-predictthe lag lengthrespectivelyinoursimulations.

A Common-feature approach for testing present-value restrictions with financial data

It is well known that cointegration between the level of two variables (labeled Yt and yt in this paper) is a necessary condition to assess the empirical validity of a present-value model (PV and PVM, respectively, hereafter) linking them. The work on cointegration has been so prevalent that it is often overlooked that another necessary condition for the PVM to hold is that the forecast error entailed by the model is orthogonal to the past. The basis of this result is the use of rational expectations in forecasting future values of variables in the PVM. If this condition fails, the present-value equation will not be valid, since it will contain an additional term capturing the (non-zero) conditional expected value of future error terms. Our article has a few novel contributions, but two stand out. First, in testing for PVMs, we advise to split the restrictions implied by PV relationships into orthogonality conditions (or reduced rank restrictions) before additional tests on the value of parameters. We show that PV relationships entail a weak-form common feature relationship as in Hecq, Palm, and Urbain (2006) and in Athanasopoulos, Guillén, Issler and Vahid (2011) and also a polynomial serial-correlation common feature relationship as in Cubadda and Hecq (2001), which represent restrictions on dynamic models which allow several tests for the existence of PV relationships to be used. Because these relationships occur mostly with nancial data, we propose tests based on generalized method of moment (GMM) estimates, where it is straightforward to propose robust tests in the presence of heteroskedasticity. We also propose a robust Wald test developed to investigate the presence of reduced rank models. Their performance is evaluated in a Monte-Carlo exercise. Second, in the context of asset pricing, we propose applying a permanent-transitory (PT) decomposition based on Beveridge and Nelson (1981), which focus on extracting the long-run component of asset prices, a key concept in modern nancial theory as discussed in Alvarez and Jermann (2005), Hansen and Scheinkman (2009), and Nieuwerburgh, Lustig, Verdelhan (2010). Here again we can exploit the results developed in the common cycle literature to easily extract permament and transitory components under both long and also short-run restrictions. The techniques discussed herein are applied to long span annual data on long- and short-term interest rates and on price and dividend for the U.S. economy. In both applications we do not reject the existence of a common cyclical feature vector linking these two series. Extracting the long-run component shows the usefulness of our approach and highlights the presence of asset-pricing bubbles.

Constructing common-factor portfolios

In this paper we construct common-factor portfolios using a novel linear transformation of standard factor models extracted from large data sets of asset returns. The simple transformation proposed here keeps the basic properties of the usual factor transformations, although some new interesting properties are further attached to them. Some theoretical advantages are shown to be present. Also, their practical importance is confirmed in two applications: the performance of common-factor portfolios are shown to be superior to that of asset returns and factors commonly employed in the finance literature.

Using common features to understand the behavior of metal-commodity prices and forecast them at different horizons

The objective of this article is to study (understand and forecast) spot metal price levels and changes at monthly, quarterly, and annual horizons. The data to be used consists of metal-commodity prices in a monthly frequency from 1957 to 2012 from the International Financial Statistics of the IMF on individual metal series. We will also employ the (relatively large) list of co-variates used in Welch and Goyal (2008) and in Hong and Yogo (2009) , which are available for download. Regarding short- and long-run comovement, we will apply the techniques and the tests proposed in the common-feature literature to build parsimonious VARs, which possibly entail quasi-structural relationships between different commodity prices and/or between a given commodity price and its potential demand determinants. These parsimonious VARs will be later used as forecasting models to be combined to yield metal-commodity prices optimal forecasts. Regarding out-of-sample forecasts, we will use a variety of models (linear and non-linear, single equation and multivariate) and a variety of co-variates to forecast the returns and prices of metal commodities. With the forecasts of a large number of models (N large) and a large number of time periods (T large), we will apply the techniques put forth by the common-feature literature on forecast combinations. The main contribution of this paper is to understand the short-run dynamics of metal prices. We show theoretically that there must be a positive correlation between metal-price variation and industrial-production variation if metal supply is held fixed in the short run when demand is optimally chosen taking into account optimal production for the industrial sector. This is simply a consequence of the derived-demand model for cost-minimizing firms. Our empirical evidence fully supports this theoretical result, with overwhelming evidence that cycles in metal prices are synchronized with those in industrial production. This evidence is stronger regarding the global economy but holds as well for the U.S. economy to a lesser degree. Regarding forecasting, we show that models incorporating (short-run) commoncycle restrictions perform better than unrestricted models, with an important role for industrial production as a predictor for metal-price variation. Still, in most cases, forecast combination techniques outperform individual models.