Econometric Institute Reprint Series

Service parts inventory control with lateral transshipment and pipeline stockflexibility (Article)

Yang, G. — 2013-04-01T00:00:00Z

In equipment-intensive industries such as truck, electronics, aircraft and dredging vessel manufacturing, service parts are often slow moving items for which the transshipment time is not negligible. However, this aspect is hardly considered in the existing service logistics literature. In this paper, we consider this aspect and propose a customer-oriented service measure which takes into account pipeline stock and lateral transshipment flexibility. We provide an approximation method for optimizing the stock allocation subject to this service measure. Via extensive numerical experiments, we show that our approximation performs very well with respect to both system performance and costs. Moreover, our numerical experiments indicate that including lateral transshipments and pipeline stock flexibility in inventory decisions is more beneficial than lateral transshipments alone. This effect is larger for high demand rates and high lateral transshipment costs. Results from a case study in the dredging industry confirm our findings. We therefore recommend introduction of pipeline stock information such as the track and trace information from freight carriers in existing ERP systems.

Forecasting the Yield Curve in a Data-Rich Environment Using the Factor-Augmented Nelson-Siegel Model (Article)

Exterkate, P. — 2013-04-01T00:00:00Z

This paper compares various ways of extracting macroeconomic information from a data-rich environment for forecasting the yield curve using the Nelson-Siegel model. Five issues in extracting factors from a large panel of macro variables are addressed; namely, selection of a subset of the available information, incorporation of the forecast objective in constructing factors, specification of a multivariate forecast objective, data grouping before constructing factors, and selection of the number of factors in a data-driven way. Our empirical results show that each of these features helps to improve forecast accuracy, especially for the shortest and longest maturities. Factor-augmented methods perform well in relatively volatile periods, including the crisis period in 2008-9, when simpler models do not suffice. The macroeconomic information is exploited best by partial least squares methods, with principal component methods ranking second best. Reductions of mean squared prediction errors of 20-30% are attained, compared to the Nelson-Siegel model without macro factors.

Centrality, flexibility and floating stocks: A quantitative evaluation of port-of-entry choices (Article)

Asperen, E. van — 2013-03-01T00:00:00Z

Ports provide a number of logistical choices concerning storage, onward transport and postponement. We investigate the flexibility offered by ports of a central location with respect to hinterland transport. This is illustrated through a case in which a number of alternative strategies are evaluated by means of simulation. We provide a simulation model and illustrate it with a case using detailed cost data, which allows us to quantify the value of the rerouting alternatives. A strategy that employs regional distribution centers coupled with a European Distribution Center results in the lowest cost per container. The superiority of this policy over standard centralized or decentralized distribution networks is largely based on the optimal balance between inventory and transportation cost, and the flexibility it offers.

Real-Time Inflation Forecasting in a Changing World (Article)

Groen, J.J.J. — 2013-01-28T00:00:00Z

This article revisits the accuracy of inflation forecasting using activity and expectations variables. We apply Bayesian model averaging across different regression specifications selected from a set of potential predictors that includes lagged values of inflation, a host of real activity data, term structure data, (relative) price data, and surveys. In this model average, we can entertain different channels of structural instability, by either incorporating stochastic breaks in the regression parameters of each individual specification within this average, or allowing for breaks in the error variance of the overall model average, or both. Thus, our framework simultaneously addresses structural change and model uncertainty that would unavoidably affect any inflation forecast model. The different versions of our framework are used to model U.S. personal consumption expenditures (PCE) deflator and gross domestic product (GDP) deflator inflation rates for the 1960–2011 period. A real-time inflation forecast evaluation shows that averaging over many predictors in a model that at least allows for structural breaks in the error variance results in very accurate point and density forecasts, especially for the post-1984 period. Our framework is especially useful when forecasting, in real-time, the likelihood of lower-than-usual inflation rates over the medium term. This article has online supplementary materials.

Do statistical forecasting models for SKU-level data benefit from including past expert knowledge? (Article)

Franses, Ph.H.B.F. — 2013-01-01T00:00:00Z

We determine whether statistical model forecasts of SKU level sales data can be improved by formally including past expert knowledge in the model as additional variables. Upon analyzing various forecasts in a large database, using various models, forecast samples and accuracy measures, we demonstrate that experts' knowledge, on average, apparently is not associated with variables which are systematically omitted from the statistical models. We also find that the formal inclusion of past judgment can be helpful in cases when the model performs poorly. This can lead to an improved interaction between models and experts, and we discuss the design features of a forecasting support system.

A class of adaptive importance sampling weighted EM algorithms for efficient and robust posterior and predictive simulation (Article)

Hoogerheide, L.F. — 2012-12-01T00:00:00Z

A class of adaptive sampling methods is introduced for efficient posterior and predictive simulation. The proposed methods are robust in the sense that they can handle target distributions that exhibit non-elliptical shapes such as multimodality and skewness. The basic method makes use of sequences of importance weighted Expectation Maximization steps in order to efficiently construct a mixture of Student-t densities that approximates accurately the target distribution-typically a posterior distribution, of which we only require a kernel-in the sense that the Kullback-Leibler divergence between target and mixture is minimized. We label this approach Mixture of t by Importance Sampling weighted Expectation Maximization (MitISEM). The constructed mixture is used as a candidate density for quick and reliable application of either Importance Sampling (IS) or the Metropolis-Hastings (MH) method. We also introduce three extensions of the basic MitISEM approach. First, we propose a method for applying MitISEM in a sequential manner, so that the candidate distribution for posterior simulation is cleverly updated when new data become available. Our results show that the computational effort reduces enormously, while the quality of the approximation remains almost unchanged. This sequential approach can be combined with a tempering approach, which facilitates the simulation from densities with multiple modes that are far apart. Second, we introduce a permutation-augmented MitISEM approach. This is useful for importance or Metropolis-Hastings sampling from posterior distributions in mixture models without the requirement of imposing identification restrictions on the model's mixture regimes' parameters. Third, we propose a partial MitISEM approach, which aims at approximating the joint distribution by estimating a product of marginal and conditional distributions. This division can substantially reduce the dimension of the approximation problem, which facilitates the application of adaptive importance sampling for posterior simulation in more complex models with larger numbers of parameters. Our results indicate that the proposed methods can substantially reduce the computational burden in econometric models like DCC or mixture GARCH models and a mixture instrumental variables model.

Variable selection and functional form uncertainty in cross-country growth regressions (Article)

Salimans, T. — 2012-12-01T00:00:00Z

Regression analyses of cross-country economic growth data are complicated by two main forms of model uncertainty: the uncertainty in selecting explanatory variables and the uncertainty in specifying the functional form of the regression function. Most discussions in the literature address these problems independently, yet a joint treatment is essential. We present a new framework that makes such a joint treatment possible, using flexible nonlinear models specified by Gaussian process priors and addressing the variable selection problem by means of Bayesian model averaging. Using this framework, we extend the linear model to allow for parameter heterogeneity of the type suggested by new growth theory, while taking into account the uncertainty in selecting explanatory variables. Controlling for variable selection uncertainty, we confirm the evidence in favor of parameter heterogeneity presented in several earlier studies. However, controlling for functional form uncertainty, we find that the effects of many of the explanatory variables identified in the literature are not robust across countries and variable selections.

The Effect of Recessions on Gambling Expenditures (Article)

Horváth, C. — 2012-12-01T00:00:00Z

This article examines the influence of the business cycle on expenditures of three major types of legalized gambling activities: Casino gambling, lottery, and pari-mutuel wagering. Empirical results are obtained using monthly aggregated US per capita consumption time series for the period 1959. 01-2010. 08. Among the three gambling activities only lottery consumption appears to be recession-proof. This series is characterized by a vast and solid growth that exceeds the growth in income and the growth in other gambling sectors. Casino gambling expenditures show a positive growth during expansions and no growth during recessions. Hence, the loss in income during recessions affects casino gambling. However, income shocks which are not directly related to the business cycle do not influence casino gambling expenditures. Pari-mutuel wagering displays an overall negative trend and its average growth rate is smaller than the growth in income, especially during recessions. The findings of this article provide important implications for the gambling industry and for local governments.

Modeling dynamic effects of promotion on interpurchase times (Article)

Fok, D. — 2012-11-01T00:00:00Z

Dynamic effects of marketing-mix variables on interpurchase times can be analyzed in the context of a duration model. Specifically, this can be done by extending the accelerated failure-time model with an autoregressive structure. An important feature of the model is that it allows for different long-run and short-run effects of marketing-mix variables on interpurchase times. The error-correction specification of the model contains parameters which measure the direct effect of a temporary change in a marketing-mix variable on interpurchase times and parameters which measure the long-run (cumulative) effect of a temporary change in a marketing-mix variable on current and future interpurchase times. As marketing efforts usually change during the spells, time-varying covariates are explicitly dealt with. Heterogeneity of individual behavior is allowed for through a mixture approach. An empirical analysis of purchases in three different categories reveals, for some segments of households, that the short-run effects of marketing-mix variables are significantly different from the long-run effects. The decay in the effect of changes in marketing-mix variables over time is larger in categories with large interpurchase times, and price has the largest long-run effect for the perishable product. Finally, ignoring dynamic effects leads to erroneous results about the effectiveness of marketing instruments.

Integrated market selection and production planning: Complexity and solution approaches (Article)

Heuvel, W. van den — 2012-09-01T00:00:00Z

Emphasis on effective demand management is becoming increasingly recognized as an important factor in operations performance. Operations models that account for supply costs and constraints as well as a supplier's ability to influence demand characteristics can lead to an improved match between supply and demand. This paper presents a class of optimization models that allow a supplier to select, from a set of potential markets, those markets that provide maximum profit when production/procurement economies of scale exist in the supply process. The resulting optimization problem we study possesses an interesting structure and we show that although the general problem is NP -complete, a number of relevant and practical special cases can be solved in polynomial time. We also provide a computationally very efficient and intuitively attractive heuristic solution procedure that performs extremely well on a large number of test instances.

One size does not fit all: Selling firms to private equity versus strategic acquirers (Article)

Roosenboom, P.G.J. — 2012-09-01T00:00:00Z

This paper investigates the selling process of firms acquired by private equity versus strategic buyers. In a single regression setup we show that selling firms choose between formal auctions, controlled sales and private negotiations to fit their firm and deal characteristics including profitability, R&D, deal initiation and type of the eventual acquirer (private equity or strategic buyer). At the same time, a regression model determining the buyer type shows that private equity buyers pursue targets that have more tangible assets, lower market-to-book ratios and lower research and development expenses relative to targets bought by strategic buyers. To reflect possible interdependencies between these two choices and their impact on takeover premium, as a last step, we estimate a simultaneous model that includes the selling mechanism choice, buyer type and premium equations. Our results show that the primary decision within the whole selling process is the target firm's decision concerning whether to sell the firm in an auction, controlled sale or negotiation which then affects the buyer type. These two decisions seem to be optimal as then they do not impact premium.

Inequality amongst the wealthiest and its link with economic growth (Article)

Franses, Ph.H.B.F. — 2012-08-01T00:00:00Z

In this article, we correlate the key features of the distribution of wealth of the 500 wealthiest individuals in the Netherlands with economic growth and stock market returns for the period 1998 to 2009. We show that each year the distribution obeys a power law and that the key parameter measures the degree of inequality. Our main finding is that more inequality amongst the wealthiest is associated with higher economic growth.

Optimal portfolios with minimum capital requirements (Article)

Santos, A.A.P. — 2012-07-01T00:00:00Z

We propose a novel approach to active risk management based on the recent Basel II regulations to obtain optimal portfolios with minimum capital requirements. In order to avoid regulatory penalties due to an excessive number of Value-at-Risk (VaR) violations, capital requirements are minimized subject to a given number of violations over the previous trading year. Capital requirements are based on the recent Basel II amendments to account for the 'stressed' VaR, that is, the downside risk of the portfolio under extreme adverse market conditions. An empirical application for two portfolios involving different types of assets and alternative stress scenarios demonstrates that the proposed approach delivers an improved balance between capital requirement levels and the number of VaR exceedances. Furthermore, the risk-adjusted performance of the proposed approach is superior to that of minimum-VaR and minimum-stressed VaR portfolios.

Consensus strategies for signed profiles on graphs (Article)

Balakrishnan, K. — 2012-06-15T00:00:00Z

The median problem is a classical problem in Location Theory: one searches for a location that minimizes the average distance to the sites of the clients. This is for desired facilities as a distribution center for a set of warehouses. More recently, for obnoxious facilities, the antimedian was studied. Here one maximizes the average distance to the clients. In this paper the mixed case is studied. Clients are represented by a profile, which is a sequence of vertices with repetitions allowed. In a signed profile each element is provided with a sign from <+,-> Thus one can take into account whether the client prefers the facility (with a + sign) or rejects it (with a - sign). The graphs for which all median sets, or all antimedian sets, are connected are characterized. Various consensus strategies for signed profiles are studied, amongst which Majority, Plurality and Scarcity. Hypercubes are the only graphs on which Majority produces the median set for all signed profiles. Finally, the antimedian sets are found by the Scarcity Strategy on e.g. Hamming graphs, Johnson graphs and halfcubes.

Consensus strategies for signed profiles on graphs (Article)

Balakrishnan, K. — 2012-06-15T00:00:00Z

The median problem is a classical problem in Location Theory: one searches for a location that minimizes the average distance to the sites of the clients. This is for desired facilities as a distribution center for a set of warehouses. More recently, for obnoxious facilities, the antimedian was studied. Here one maximizes the average distance to the clients. In this paper the mixed case is studied. Clients are represented by a profile, which is a sequence of vertices with repetitions allowed. In a signed profile each element is provided with a sign from (+,-). Thus one can take into account whether the client prefers the facility (with a + sign) or rejects it (with a - sign). The graphs for which all median sets, or all antimedian sets, are connected are characterized. Various consensus strategies for signed profiles are studied, amongst which Majority, Plurality and Scarcity. Hypercubes are the only graphs on which Majority produces the median set for all signed profiles. Finally, the antimedian sets are found by the Scarcity Strategy on e.g. Hamming graphs, Johnson graphs and halfcubes.

Private Equity Recommitment Strategies for Institutional Investors (Article)

Zwart, G.J. de — 2012-05-01T00:00:00Z

Institutional investors must deal with irrevocable commitments, cash flow uncertainty, and illiquidity when making new commitments to maintain their portfolio exposure to private equity funds. This study develops a dynamic recommitment strategy to preserve the strategic allocation to private equity. For each period, the level of new commitments is determined by characteristics of the existing private equity portfolio, including received distributions, uncalled capital from old commitments, and the current allocation relative to its target level. [PUBLICATION ABSTRACT]

Modeling seasonality in new product diffusion (Article)

Peers, Y. — 2012-03-01T00:00:00Z

We propose a method to include seasonality in any diffusion model that has a closed-form solution. The resulting diffusion model captures seasonality in a way that naturally matches the original diffusion model's pattern. The method assumes that additional sales at seasonal peaks are drawn from previous or future periods. This implies that the seasonal pattern does not influence the underlying diffusion pattern. The model is compared with alternative approaches through simulations and empirical examples. As alternatives, we consider the standard Generalized Bass Model (GBM) and the basic Bass Model, which ignores seasonality. One of the main findings is that modeling seasonality in a GBM generates good predictions but gives biased estimates. In particular, the market potential parameter is underestimated. Ignoring seasonality in cases where data of the entire diffusion period are available gives unbiased parameter estimates in most relevant scenarios. However, ignoring seasonality leads to biased parameter estimates and predictions when only part of the diffusion period is available. We demonstrate that our model gives correct estimates and predictions even if the full diffusion process is not yet available.

The effectiveness of high-frequency direct-response commercials (Article)

Kiygi Calli, M. — 2012-03-01T00:00:00Z

To optimally schedule commercials for a car repair service, we investigate the impact of direct-response commercials on incoming calls at a national call center by using a unique hourly data set from a Belgium-based company. We address the question of whether advertising effects vary across the hours of the week and thereby provide opportunities for the company to optimize its media plan. We summarize the data with a random-effects hierarchical linear model that treats the hours within the week as a panel of 168 interrelated time series. This model highlights the intraday and intraweek heterogeneity of advertising elasticities.

Supply and demand effects in television viewing. A time series analysis (Article)

Vergeer, M. — 2012-03-01T00:00:00Z

In this study we analyze daily data on television viewing in the Netherlands. We postulate hypotheses on supply and demand factors that could impact the amount of daily viewing time. Although the general assumption is that supply and demand often correlate, we see that for television this is only marginally the case. Especially diversity of program supply, often deemed very important in media markets, does not affect (positively or negatively) television viewing behavior. Most variation in television viewing can be attributed to habit and to regular events (e. g. weekends, Christmas) and to unexpected events (e. g. the 9/11 WTC attack). We also find that weather conditions interact with program types, so that, for example, in winter times people favor entertainment programs even more, suggesting that people use television for mood management.

Do vendors benefit from promotions in a multi-vendor loyalty program? (Article)

Dorotic, M. — 2011-11-01T00:00:00Z

The growing trend of networking in recent years has led to an increase in number of loyalty program partnerships, most notably multi-vendor loyalty programs (MVLP). In an MVLP (as in other types of LPs), cardholders frequently receive promotional mailings intended to increase sales at the participating vendors. This study examines individual vendor and joint (multiple vendors) promotions on the sales performance of five main vendors within an MVLP. Findings of the study indicate low responsiveness of cardholders to LP-induced promotions. The responsiveness may be improved if multiple communication channels are used jointly to present an individual-vendor promotion. Moreover, this is one of the first empirical studies to investigate potential networking benefits of coalitions in an MVLP. Empirical evidence of coalition benefits of promotions is lacking, because we find neither stronger effects for joint-relative to individual promotions nor significant spillover effects of promotions across vendors (i. e., cross-vendor effects). The current study offers potential explanations for these findings.