A flexible parametric GARCH model with an application to exchange rates

Many asset prices, including exchange rates, exhibit periods of stability punctuated by infrequent, substantial, often one‐sided adjustments. Statistically, this generates empirical distributions of exchange rate changes that exhibit high peaks, long tails, and skewness. This paper introduces a GARCH model, with a flexible parametric error distribution based on the exponential generalized beta (EGB) family of distributions. Applied to daily US dollar exchange rate data for six major currencies, evidence based on a comparison of actual and predicted higher‐order moments and goodness‐of‐fit tests favours the GARCH‐EGB2 model over more conventional GARCH‐t and EGARCH‐t model alternatives, particularly for exchange rate data characterized by skewness. Copyright © 2001 John Wiley & Sons, Ltd.     

An empirical test of a correspondence model of expatriate managers' work adjustment

We develop and empirically test a model of expatriate managers' work adjustment. In this model we relate the fit between work-related abilities and needs of expatriate managers as well as the fit between the job requirements of, and incentives associated with, an international assignment to the level of expatriate managers' work adjustment. We test this model with data gathered by means of an electronic survey among 118 German expatriate managers. The empirical findings largely support our theoretical model. The paper enhances our understanding of expatriate managers' work adjustment and its antecedents and contributes to the theoretical and empirical basis of research into expatriate management.     

Labour adjustment costs: Estimation of a dynamic discrete choice model using panel data for Greek manufacturing firms

In this paper we estimate a dynamic structural model of employment at firm level. Our dataset consists of a balanced panel of 2790 Greek manufacturing firms. The empirical evidence of this dataset stresses three important stylized facts: (a) there are periods in which firms decide not to change their labour input, (b) there are periods of large employment changes (lumpy nature of labour adjustment) and (c) the commonality is employment spikes to be followed by smooth and low employment growth periods. Following Cooper and Haltiwanger [Cooper, R.W. and Haltiwanger, J. “On the Nature of Capital Adjustment Costs”, Review of Economic Studies, 2006; 73(3); 611–633], we consider a dynamic discrete choice model of a general specification of adjustment costs including convex, non-convex and “disruption of production” components. We use a method of simulated moments procedure to estimate the structural parameters. Our results indicate considerable fixed costs in the Greek employment adjustment.     

Do adjustment costs explain investment-cash flow insensitivity?

In this paper, I explain two “puzzles” that have been observed in firm level data. First, firms that display a high sensitivity of investment to cash flow (commonly believed to be an indicator of liquidity constraints) usually have large unutilized lines of credit which, presumably, could be used to overcome the shortage of funds. Second, firms that are perceived to be extremely liquidity constrained actually show very little sensitivity of investment to cash flow.I show how a dynamic model of firm investment with liquidity constraints and non-convex costs of adjustment of capital can explain these facts. These two features together imply that firms need to have a certain threshold level of financial resources before they can afford to increase investment. Once they cross this threshold, firms’ investment will be positively correlated with their financial resources until they reach their desired level of capital stock. However, even if investment is sensitive to cash flow, firms may borrow below their credit limit to guard against future bankruptcy or binding liquidity constraints.     

Transaction Costs,Option Prices,and Model Risk in Fair Value Accounting

This paper examines the reliability of option fair value estimates in the presence of transaction costs. The Black Scholes Merton (BSM) framework assumes zero transaction costs and thus might not provide a reasonable approximation in this context. We investigate the model adjustments companies make to their BSM models to deal with these transaction costs. We specifically examine Employee Stock Option (ESO) plans listed on the French stock exchange, as detailed disclosure on modeling is available for these ESOs. Our analysis questions the reliability of these model adjustments, especially their bias and the extent to which they provide a faithful representation of option fair values. Holding parameter values constant, we find that the model adjustments lead to a median understatement of 52% compared to the BSM model price, higher than the discount we observe for the opportunistic determination of model parameters (below 20%). The paper contributes to the fair value literature by highlighting model risk in the fair valuation of options. This model risk stems from assumptions made about the size of transaction costs and complements the notion of parameter risk analyzed in previous literature. As a result, the model itself might be a possible channel for fair value management.     

What do interest rates reveal about the functioning of real business cycle models?

This paper begins by documenting the extent to which the predictions of standard Real Business Cycle (RBC) models are incompatible with observed movements in real interest rates. The main finding of the paper is that extending the baseline model to include habit persistence in consumption and adjustment costs to capital significantly improves the model's empirical performance. In our evaluation of the model's performance, we take special care of estimating and testing predictions of the model using both moments drawn directly from the data and moments calculated after identifying shocks to the stochastic trend.     

Asymmetric convergence in US financial credit default swap sector index markets

This study examines the asymmetric adjustments to the long-run equilibrium for credit default swap (CDS) sector indexes of three financial sectors – banking, financial services and insurance – in the presence of a threshold effect. The results of the momentum-threshold autoregression (M-TAR) models demonstrate that asymmetric cointegration exists for all pairs comprised of those three CDS indexes. The speeds of adjustment in the long-run are much higher in the case of adjustments from below the threshold than from above for all the pairs. The estimates of The MTAR-VEC models suggest that the dual CDS index return in each sector pair participates in the adjustment to equilibrium in the short- and long-run taken together. But in the long-run alone, only one of the two spreads in each pair participates. Policy implications are also provided.     

Revisiting the effect of household size on consumption over the life-cycle

Although the link between household size and consumption has strong empirical support, there is no consistent way in which demographics are dealt with in standard life-cycle models. We study the relationship between the predictions of the Single Agent model (the standard in the literature) versus a simple model extension (the Demographics model) where deterministic changes in household size and composition affect optimal consumption decisions. We show theoretically that the Demographics model is conceptually preferable to the Single Agent model as it captures economic mechanisms ignored by the latter. However, our quantitative analysis demonstrates that differences in predictions for consumption are negligible across models, when using standard calibration strategies. This suggests that it is largely irrelevant which model specification is used.     

Price rigidity: An exploration of the demand side

This paper presents an exploration of the demand-side effects of unanticipated price changes. Consumers faced with these changes may have to reoptimize their income allocation. Reoptimization is costly, and reoptimization costs result in kinked demand curves. The existence of such kinked demands provides an additional explanation of the observed nominal price rigidity. In addition, examination of unexpected nominal price changes during inflationary periods provides some justification as to why nominal price adjustments are large, infrequent and almost never downward.     

DSGE Models in the Frequency Domains

We use frequency domain techniques to estimate a medium‐scale dynamic stochastic general equilibrium (DSGE) model on different frequency bands. We show that goodness of fit, forecasting performance and parameter estimates vary substantially with the frequency bands over which the model is estimated. Estimates obtained using subsets of frequencies are characterized by significantly different parameters, an indication that the model cannot match all frequencies with one set of parameters. In particular, we find that: (i) the low‐frequency properties of the data strongly affect parameter estimates obtained in the time domain; (ii) the importance of economic frictions in the model changes when different subsets of frequencies are used in estimation. This is particularly true for the investment adjustment cost and habit persistence: when low frequencies are present in the estimation, the investment adjustment cost and habit persistence are estimated to be higher than when low frequencies are absent. Copyright © 2014 John Wiley & Sons, Ltd.     

ECONOMETRIC MODELS OF ASYMMETRIC PRICE TRANSMISSION

Abstract In this paper, we review the existing empirical literature on price asymmetries in commodities, providing a way to classify and compare different studies that 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 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. Each empirical study is then critically discussed in the light of this new classification of asymmetries. Third, 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. Finally, we use the meta‐regression analysis to investigate whether the results of asymmetry tests are not model‐invariant and find which additional factors systematically influence the rejection of the null hypothesis of symmetric price adjustment. The main results of our survey can be summarized as follows: (i) each econometric model is specialized to capture a subset of asymmetries; (ii) each asymmetry is better investigated by a subset of econometric models; (iii) the general significance of the F test for asymmetric price transmission depends mainly on characteristics of the data, dynamic specification of the econometric model, and market characteristics. Overall, our empirical findings confirm that asymmetry, in all its forms, is very likely to occur in a wide range of markets and econometric models.     

Endogenous business cycle propagation and the persistence problem: The role of labor-market frictions

Contrasting sharply with a recent trend in DSGE modeling, we propose a business cycle model where frictions and shocks are chosen with parsimony. The model emphasizes a few labor-market frictions and shocks to monetary policy and technology. The model, estimated from U.S. quarterly postwar data, accounts well for important differences in the serial correlation of the growth rates of aggregate quantities, the size of aggregate fluctuations and key comovements, including the correlation between hours and labor productivity. Despite its simplicity, the model offers an answer to the persistence problem (Chari et al., 2000) that does not rely on multiple frictions and adjustment lags or ad hoc backward-looking components. We conclude modern DSGE models need not embed large batteries of frictions and shocks to account for the salient features of postwar business cycles.     

Forecasting with approximate dynamic factor models: The role of non-pervasive shocks

This paper studies the role of non-pervasive shocks when forecasting with factor models. To this end, we first introduce a new model that incorporates the effects of non-pervasive shocks, an Approximate Dynamic Factor Model with a sparse model for the idiosyncratic component. Then, we test the forecasting performance of this model both in simulations, and on a large panel of US quarterly data. We find that, when the goal is to forecast a disaggregated variable, which is usually affected by regional or sectorial shocks, it is useful to capture the dynamics generated by non-pervasive shocks; however, when the goal is to forecast an aggregate variable, which responds primarily to macroeconomic, i.e. pervasive, shocks, accounting for non-pervasive shocks is not useful.     

Carbon Financial Instruments, thin trading, and volatility: Evidence from the Chicago Climate Exchange

We provide the first econometric investigation of volatility dynamics for the Carbon Financial Instrument (CFI) traded on the Chicago Climate Exchange (CCX). A CFI is a financial contract with the right to emit 100 metric tons of CO₂ equivalent. In this study, we present evidence of infrequent trading in the CCX, consistent with emerging markets that are inhabited by non-competitive agents trading permits. We explore the relationship between the observed thin trading effects and GARCH model testing and estimation, concluding with some implications for volatility-based Value-at-Risk forecasts. Our results are important for traders of Carbon Financial Instruments and for policy makers seeking to improve the design of the Chicago Climate Exchange.     

Inferring monetary policy objectives with a partially observed state

Accounting for the uncertainty in real-time perceptions of the state of the economy is believed to be critical for monetary policy analysis. We investigate this claim through the lens of a New Keynesian model with optimal discretionary policy and partial information. Structural parameters are estimated using a data set that includes real-time and ex post revised observations spanning 1965–2010. In comparison to a standard complete information model, our estimates reveal that under partial information: (i) the Federal Reserve demonstrates a significant concern for stabilizing the output gap after 1979, (ii) the model׳s fit with revised data improves, and (iii) the tension between optimal and observed policy is smaller.     

Some model-restricted shrinkage estimators for contingency tables with missing data

For contingency tables with extensive missing data, the unrestricted MLE under the saturated model, computed by the EM algorithm, is generally unsatisfactory. In this case, it may be better to fit a simpler model by imposing some restrictions on the parameter space. Perlman and Wu (1999) propose lattice conditional independence (LCI) models for contingency tables with arbitrary missing data patterns. When this LCI model fits well, the restricted MLE under the LCI model is more accurate than the unrestricted MLE under the saturated model, but not in general. Here we propose certain empirical Bayes (EB) estimators that adaptively combine the best features of the restricted and unrestricted MLEs. These EB estimators appear to be especially useful when the observed data is sparse, even in cases where the suitability of the LCI model is uncertain. We also study a restricted EM algorithm (called the ER algorithm) with similar desirable features. Received: July 1999     

Estimating the LQAC model with I(2) variables

This paper derives a method for estimating and testing the Linear Quadratic Adjustment Cost (LQAC) model when the target variable and some of the forcing variables follow I(2) processes. Based on a forward-looking error-correction formulation of the model it is shown how to obtain strongly consistent estimates of the structural parameters from both a linear and a non-linear cointegrating regression where first-differences of the I(2) variables are included as regressors (multicointegration). Further, based on the estimated parameter values, it is shown how to test and evaluate the LQAC model using a VAR approach. A simple easy interpretable metric for measuring the model fit is suggested. In an empirical application using UK money demand data, the non-linear multicointegrating regression delivers an economically plausible estimate of the adjustment cost parameter. However, the restrictions implied by the exact LQAC model under rational expectations are strongly rejected and the metric for model fit indicates a substantial noise component in the model. Copyright © 1999 John Wiley & Sons, Ltd.     

Goodness of fit in confirmatory factor analysis: The effects of sample size and model parsimony

The purpose of the present investigation is to examine the influence of sample size (N) and model parsimony on a set of 22 goodness-of-fit indices including those typically used in confirmatory factor analysis and some recently developed indices. For sample data simulated from two known population data structures, values for 6 of 22 fit indices were reasonably independent ofN and were not significantly affected by estimating parameters known to have zero values in the population: two indices based on noncentrality described by McDonald (1989; McDonald and Marsh, 1990), a relative (incremental) index based on noncentrality (Bentler, 1990; McDonald & Marsh, 1990), unbiased estimates of LISREL's GFI and AGFI (Joreskog & Sorbom, 1981) presented by Steiger (1989, 1990) that are based on noncentrality, and the widely known relative index developed by Tucker and Lewis (1973). Penalties for model complexity designed to control for sampling fluctuations and to address the inevitable compromise between goodness of fit and model parsimony were evaluated.     

Multicointegration in Stock-Flow Models

Multicointegration, in the sense of Granger and Lee (1990), frequently occurs in models of stock-flow adjustment and implies cointegration amongst I(2) variables and their differences (polynomial cointegration). The purpose of this article is two-fold. First, we demonstrate that based on a multicointegrated vector autoregression (VAR) two equivalent error correction model (ECM) representations can be derived; the first is expressed in terms of adjustments in the flows of the variables (the standard I(2) ECM), and the second is expressed in terms of adjustments in both the stocks and the flows. Secondly, we apply I(2) estimation and testing procedures for multicointegrated time series to analyze data for US housing construction. We find that stocks of housing units started and completed exhibit poly- nomial cointegration (and hence the flows are multicointegrated) and the associated ECM's are estimated. Lee (1992, 1996) also found multicointegration in this data set but without explicitly exploiting the I(2) property.     

The Organizational Impact of Business Model Innovation: Assessing the Person-Organization Fit

Studies on business model innovation (BMI) have largely focused on firm performance, neglecting outcomes of BMI beyond financial performance indicators. Research lacks empirical findings from the internal organizational dynamics following the inherent transformation process induced by BMI. Rooting our analysis in configuration theory, the purpose of this paper is to shed light on the organizational impact of BMI. We employ the person-organization fit concept and assess (unintentional) changes in the fit relationship subsequent to BMI. Our findings suggest that incremental BMI enhances fit whereas radical BMI decreases it. We further discuss the theoretical and practical implications of our study.