Lender learning and entry under general demand uncertainty

In this paper, we examine the effect of potential entry on learning by a lender when the demand shock has a general distribution. We show that under this type of noise, entry does not lead to any changes in the equilibrium expected signals and therefore, there is no effect on learning by the lender, unlike the case when noise is uniformly distributed. The result holds even when contracts are not observable.     

Revisiting dividend yield dynamics and returns predictability: Evidence from a time-varying ESTR model

Since the bubble of the late 1990s the dividend yield appears non-stationary indicating the breakdown of the equilibrium relationship between prices and dividends. Two lines of research have developed in order to explain this apparent breakdown. First, that the dividend yield is better characterised as a non-linear process and second, that it is subject to mean level shifts. This paper jointly models both of these characteristics by allowing non-linear reversion to a changing mean level. Results support stationarity of this model for eight international dividend yield series. This model is than applied to the forecast of monthly stock returns. Evidence supports our time-varying non-linear model over linear alternatives, particularly so on the basis of an out-of-sample R-squared measure and a trading rule exercise. More detailed examination of the trading rule measure suggests that investors could obtain positive returns, as the model forecasts do not imply excessive trading such that costs would not outweigh returns. Finally, the superior performance of the non-linear model largely arises from its ability to forecast negative returns, whereas linear models are unable to do.     

Property value impacts of foreclosed housing acquisitions under uncertainty

Community development corporations seek to stabilize neighborhoods affected by the recent foreclosure crisis through acquisition and redevelopment of distressed properties. One rationale for this work is the alleviation or avoidance of negative foreclosure impacts. We estimate the lost value to proximate properties associated with a single foreclosure through a Markov chain representing probabilistic transitions between foreclosure stages. We apply our model to a case study of foreclosure properties in Chelsea, MA. A rank ordering by estimated property value impacts indicates significant potential gains in social value as compared to current community development practice. We extend our basic model to address the effects of clusters of foreclosed units upon the value of proximate properties. This study provides additional support for the use of decision modeling in foreclosed housing acquisition and redevelopment.     

Forecasting sales response for multiple time horizons and temporally aggregated data: A comparison of constant and stochastic coefficient models

Past research on time-varying sales-response models emphasized the application of different estimation techniques in examining variation in advertising effectiveness over time. This study focuses on comparing sales forecasts using constant and stochastic coefficients sales-response models. Selected constant and stochastic coefficient models are applied to six sets of bimonthly and one set of annual advertising and sales data to assess forecasting accuracy for time horizons of various lengths. Results show improved forecasting accuracy for a first-order autoregressive stochastic coefficient model, particularly in short-run forecasting applications.     

The macroeconomic response to real and financial factors,commodity prices,and monetary policy: International evidence

This study estimates a variety of small dynamic factor macro models where the factors are time-varying. The sample consists of 20 economies from around the world. Using quarterly data since the late 1990s, I find that the focus of some policymakers on the negative spillovers from monetary shocks is exaggerated. Four separate types of shocks are identified, and these can easily offset each other with a neutral to positive overall economic impact in some economies investigated here. However, a few economies, namely Brazil, Chile and China, experience a net economic loss from spillovers.     

Managing risk and uncertainty in complex capital projects

In evaluating capital budgeting decisions, quantitative approaches, such as traditional discounted cash flow modeling and real options valuations, are useful when there is a presumed probability distribution for the future forecasted outcomes or for when there are lower levels of uncertainty. As uncertainty increases and forecasting becomes difficult, the value of financial modeling techniques decreases. Borrowing from the strategic management literature, we argue that it may be useful to employ a qualitative approach to evaluate capital projects when faced with high levels of uncertainty. In order to illustrate our argument, we use a derivative of scenario planning and qualitative real options to evaluate non-quantifiable factors in a project for the National Ignition Facility.     

Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search

We examine the ability of online ticker searches (e.g. XOM for Exxon Mobil) to forecast abnormal stock returns and trading volumes. Specifically, we argue that online ticker searches serve as a valid proxy for investor sentiment — a set of beliefs about cash flows and investment risks that are not necessarily justified by the facts at hand — which is generally associated with less sophisticated, retail investors. Based on prior research on investor sentiment, we expect online search intensity to forecast stock returns and trading volume, and also expect that highly volatile stocks, which are more difficult to arbitrage, will be more sensitive to search intensity than less volatile stocks. In a sample of S&P 500 firms over the period 2005-2008, we find that, over a weekly horizon, online search intensity reliably predicts abnormal stock returns and trading volumes, and that the sensitivity of returns to search intensity is positively related to the difficulty of a stock being arbitraged. More broadly, our study highlights the potential of employing online search data for other forecasting applications.     

Residential mobility and job changes under uncertainty

This paper empirically investigates households' residential mobility and job change decisions under uncertainty. We allow households' degree of risk aversion to be a confounding factor in the joint decision of residential mobility and job changes. Using panel data to estimate a random effects multinomial probit model of households' joint decision of residential and job mobility, our empirical results show that risk aversion discourages a household from making any changes. Moreover, when compared to single changes in either job or residential locations, risk aversion is more discouraging for joint changes to more central residential locations and less discouraging for joint changes to more distant residential locations. These effects are statistically significant, albeit small in magnitude. Our empirical results demonstrate the uncertainty does play a role in households' job and residential mobility decisions.     

Abnormal returns, risk, and options in large data sets

Large data sets in finance with millions of observations have become widely available. Such data sets enable the construction of reliable semi-parametric estimates of the risk associated with extreme price movements. Our approach is based on semi-parametric statistical extreme value analysis, and compares favorably with the conventional finance normal distribution based approach. It is shown that the efficiency of the estimator of the extreme returns may benefit from high frequency data. Empirical tail shapes are calculated for the German Mark—US Dollar foreign exchange rate, and we use the semi-parametric tail estimates in combination with the empirical distribution function to evaluate the returns on exotic options.     

Existence of competitive equilibrium under financial constraints and increasing returns

This paper studies a ‘factor cost in advance’ model with increasing returns in production. In the model both partial equilibrium and general equilibrium may exist since working capital of firms limit their input demand. We provide a sufficient condition for the existence of partial equilibrium of a firm operating on a non-convex choice set. Furthermore we establish the existence and uniqueness of competitive equilibrium in the special case of logarithmic utility.     

Dynamic portfolio choice under ambiguity and regime switching mean returns

I examine a continuous-time intertemporal consumption and portfolio choice problem under ambiguity, where expected returns of a risky asset follow a hidden Markov chain. Investors with Chen and Epstein's (2002) recursive multiple priors utility possess a set of priors for unobservable investment opportunities. The optimal consumption and portfolio policies are explicitly characterized in terms of the Malliavin derivatives and stochastic integrals. When the model is calibrated to U.S. stock market data, I find that continuous Bayesian revisions under incomplete information generate ambiguity-driven hedging demands that mitigate intertemporal hedging demands. In addition, ambiguity aversion magnifies the importance of hedging demands in the optimal portfolio policies. Out-of-sample experiments demonstrate the economic importance of accounting for ambiguity.     

Sequential decisions under uncertainty and the maximum theorem

For sequential decision problems in which the decision-maker observes a process of state variables and chooses an adapted process of action variables, the paper defines a topology on the space of measures of processes of state variables which ensures the applicability of Berge's maximum theorem to the decision-maker's optimal behavior. The topology controls for the information available to the decision-maker at each decision date. The paper also discusses the implications of the analysis for the dynamic-programming approach to sequential decision-making under uncertainty, and for equilibrium existence proof strategies in sequential-market models and games.     

Optimal capital accumulation under price uncertainty and costly reversibility

We consider the optimal capital accumulation policy of a competitive firm operating in the presence of decreasing returns to scale, price uncertainty, and costly reversibility of investment. We characterize the optimal accumulation policy and derive the value of the firm by focusing on the marginal investment decision and solving the associated optimal timing problem characterizing the option value of the associated opportunity to either disinvest or acquire a marginal unit of capacity. We also characterize the required exercise premia associated with the optimal policies and demonstrate that hysteresis prevails within this class of accumulation problems as well.     

Forecasting UK GDP growth and inflation under structural change. A comparison of models with time-varying parameters

Evidence from a large and growing body of empirical literature strongly suggests that there have been changes in the inflation and output dynamics in the United Kingdom. The majority of these papers base their results on a class of econometric models that allows for time-variation in the coefficients and volatilities of shocks. While these models have been used extensively for studying evolving dynamics and for structural analysis, there has been little evidence that they are useful for forecasting UK output growth and inflation. This paper attempts to fill this gap by comparing the performances of a wide range of time-varying parameter models in forecasting output growth and inflation. We find that allowing for time-varying parameters can lead to large and statistically significant gains in forecast accuracy.     

EKC-type transitions and environmental policy under pollutant uncertainty and cost irreversibility

Previous studies have suggested that some pollutant levels first increases due to the economic growth and then start decreasing, the pattern being called the “environmental Kuznets curve” (EKC). We examine EKC-type transitions of pollutant levels not with respect to economic growth but more generally in time. Assuming that each policy maker optimally executes the two switching options of regulation and unregulation for pollution, the switching dynamics of environmental policy can be described by an alternating renewal process. It is shown that the double Laplace transform of transition density of a pollutant level can be obtained by a novel application of renewal theory. The expected level of overall pollutants is then calculated numerically and found to exhibit either a Λ‐shaped or an N-shaped pattern in time. Our results present a simple explanation for the EKC-type transitions of pollutant levels within a real options framework.     

The competitive firm under price uncertainty: the role of information and hedging

We study the impact of transparency in a commodity market on the decision problem of a competitive firm under price uncertainty and hedging opportunities. Market transparency is modeled by means of the informational content of publicly observable signals which are correlated with the random price. We find that the impact of more transparency on labor employment and production depends on the firm’s technology. In particular, more transparency may result in lower average output even though on average more labor has been used in the production process. We also analyze the link between market transparency and the welfare of the firm. We are grateful to two anonymous referees who made extremely useful comments and suggestions.     

Optimal monetary policy under incomplete markets and aggregate uncertainty: A long-run perspective

This paper examines the role of monetary policy in an environment with aggregate risk and incomplete markets. In a two-period overlapping-generations model with aggregate uncertainty, optimal monetary policy attains the ex-ante Pareto optimal allocation. This policy aims to stabilize the savings rate in the economy by changing real returns of nominal bonds via variation in expected inflation. Optimal expected inflation is procylical and on average higher than without uncertainty. Simple inflation targeting rules closely approximate the optimal monetary policy.     

Earthquake risk and housing prices in Japan: Evidence before and after massive earthquakes

The hedonic pricing approach is used to examine whether homeowners and/or renters alter their subjective assessments of earthquake risks after massive earthquakes. Using nation-wide household panel data coupled with earthquake hazard information and records of observed earthquakes, we find that there are some modifications of individuals' assessments of earthquake risk in both cases. We have carefully taken into consideration the bias stemming from the use of objective risk variables as a proxy for individual risk assessments. Our results suggest that the price discount from locating within a quake-prone area is significantly larger soon after earthquake events than beforehand. We argue that the most likely interpretation for this result is that households tend to underestimate earthquake risk if there has not been a recent occurrence.     

Optimal consumption and investment under time-varying relative risk aversion

We consider the continuous time consumption-investment problem originally formalized and solved by Merton in case of constant relative risk aversion. We present a complete solution for the case where relative risk aversion with respect to consumption varies with time, having in mind an investor with age-dependent risk aversion. This provides a new motivation for life-cycle investment rules. We study the optimal consumption and investment rules, in particular in the case where the relative risk aversion with respect to consumption is increasing with age.