Effect fusion using model-based clustering

In social and economic studies many of the collected variables are measured on a nominal scale, often with a large number of categories. The definition of categories is usually not unambiguous and different classification schemes using either a finer or a coarser grid are possible. Categorisation has an impact when such a variable is included as covariate in a regression model: a too fine grid will result in imprecise estimates of the corresponding effects, whereas with a too coarse grid important effects will be missed, resulting in biased effect estimates and poor predictive performance. To achieve automatic grouping of levels with essentially the same effect, we adopt a Bayesian approach and specify the prior on the level effects as a location mixture of spiky normal components. Fusion of level effects is induced by a prior on the mixture weights which encourages empty components. Model-based clustering of the effects during MCMC sampling allows to simultaneously detect categories which have essentially the same effect size and identify variables with no effect at all. The properties of this approach are investigated in simulation studies. Finally, the method is applied to analyse effects of high-dimensional categorical predictors on income in Austria

Reference-based transitions in short-run price elasticity

Marketing literature has long recognized that price response need not be monotonic and symmetric, but has yet to provide generalizable market-level insights on reference price type, asymmetric thresholds and sign and magnitude of elasticity transitions. In this paper, we introduce smooth transition models to study reference-based price response across 25 fast moving consumer good categories. Our application to 100 brands shows that 77% demonstrate reference-based price response, of which 36% reflects historical reference prices, 31% reflects competitive reference prices, and 33% reflects both types of reference prices. This reference-based price response shows asymmetry for gains versus losses on three levels: the threshold size, the sign and the magnitude of the elasticity difference. For historical reference prices, the threshold size is larger for gains (20%) than for losses (12%) and the assimilation/contrast effects for gains (-0.41) are smaller than the saturation effects for losses (0.81). For competitive reference prices, the threshold size is smaller for gains (3%) than for losses (16%), and the saturation effects are larger for gains (0.33) than for losses (0.15). These results are moderated by both brand and category characteristics that affect reference price accessibility and diagnosticity. Historical reference prices more often play a role for national brands, for planned purchases and in inexpensive categories with low price volatility and high purchase frequency. When price discounting, high-share brands face larger latitudes of acceptance. When raising prices, saturation effects set in later for brands with high price volatility and for categories with high price spread and for planned purchases. As for competitive reference prices, saturation effects set in later for expensive brands with high price volatility and in categories with lower price volatility, higher price spread and higher concentration. Sales, revenue and margin implications are illustrated for price changes typically observed in consumer markets.asymmetric price thresholds;competitive versus historical reference prices;empirical generalizations;kinked demand curve;saturation versus assimilation/contrast effects;smooth-transition regression models

Employment Effects of Innovation at the Firm Level

This paper analyzes empirically the effects of innovation on employment at the firm levelusing a uniquely long panel dataset of German manufacturing firms. The overall effect ofinnovations on employment often remains unclear in theoretical contributions due to reverseeffects. We distinguish between product and process innovations and introduce in additiondifferent innovation categories. We find clearly positive effects for product and processinnovations on employment growth with the effects for process innovations being slightlyhigher. The effects are stronger in small firms and differ between firms in former West andEast Germany.innovation, labour demand, employment, firm size, panel data

Non-Keynesian effects of Government Spending: Some implications for the Stability and Growth Pact

The paper focuses on the non-Keynesian effects of fiscal policy, specifically government expenditure on output in Bulgaria. The main finding of the study is that the size of the fiscal impulse is the most important determinant of the non-Keynesian outcome. Also, the results imply that the “balanced-budget rule” does not automatically assure growth; the regulations regarding the budgetary categories themselves should also be considered.Fiscal policy; Non-Keynesian effects; balanced-budget rule; Stability and Growth Pact

Simulation of Tail Weight Distributions in Biological Year 1986–2006 Landings of Brown Shrimp, Farfantepenaeus aztecus, from the Northern Gulf of Mexico Fishery

Size distribution within re- ported landings is an important aspect of northern Gulf of Mexico penaeid shrimp stock assessments. It reflects shrimp population characteristics such as numerical abundance of various sizes, age structure, and vital rates (e.g. recruitment, growth, and mortality), as well as effects of fishing, fishing power, fishing practices, sampling, size-grading, etc. The usual measure of shrimp size in archived landings data is count (C) the number of shrimp tails (abdomen or edible portion) per pound (0.4536 kg). Shrimp are marketed and landings reported in pounds within tail count categories. Statistically, these count categories are count class intervals or bins with upper and lower limits expressed in C. Count categories vary in width, overlap, and frequency of occurrence within the landings. The upper and lower limits of most count class intervals can be transformed to lower and upper limits (respectively) of class intervals expressed in pounds per shrimp tail, w, the reciprocal of C (i.e. w = 1/C). Age based stock assessments have relied on various algorithms to estimate numbers of shrimp from pounds landed within count categories. These algorithms required un- derlying explicit or implicit assumptions about the distribution of C or w. However, no attempts were made to assess the actual distribution of C or w. Therefore, validity of the algorithms and assumptions could not be determined. When different algorithms were applied to landings within the same size categories, they produced different estimates of numbers of shrimp. This paper demonstrates a method of simulating the distribution of w in reported biological year landings of shrimp. We used, as examples, landings of brown shrimp, Farfantepenaeus aztecus, from the northern Gulf of Mexico fishery in biological years 1986–2006. Brown shrimp biological year, Ti, is defined as beginning on 1 May of the same calendar year as Ti and ending on 30 April of the next calendar year, where subscript i is the place marker for biological year. Biological year landings encompass most if not all of the brown shrimp life cycle and life span. Simulated distributions of w reflect all factors influencing sizes of brown shrimp in the landings within a given biological year. Our method does not require a priori assumptions about the parent distributions of w or C, and it takes into account the variability in width, overlap, and frequency of occurrence of count categories within the landings. Simulated biological year distributions of w can be transformed to equivalent distributions of C. Our method may be useful in future testing of previously applied algorithms and development of new estimators based on statistical estimation theory and the underlying distribution of w or C. We also examine some applications of biological year distributions of w, and additional variables derived from them

Alternative Asymmetric Stochastic Volatility Models

The stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is a generalization of the exponential GARCH (EGARCH) model of Nelson (1991). We consider categories for asymmetric effects, which describes the difference among the asymmetric effect of the EGARCH model, the threshold effects indicator function of Glosten, Jagannathan and Runkle (1992), and the negative correlation between the innovations in returns and volatility. The new model is estimated by the efficient importance sampling method of Liesenfeld and Richard (2003), and the finite sample properties of the estimator are investigated using numerical simulations. Four financial time series are used to estimate the alternative asymmetric SV models, with empirical asymmetric effects found to be statistically significant in each case. The empirical results for S&P 500 and Yen/USD returns indicate that the leverage and size effects are significant, supporting the general model. For TOPIX and USD/AUD returns, the size effect is nsignificant, favoring the negative correlation between the innovations in returns and volatility. We also consider standardized t distribution for capturing the tail behavior. The results for Yen/USD returns show that the model is correctly specified, while the results for three other data sets suggest there is scope for improvement.

"Alternative Asymmetric Stochastic Volatility Models"

The stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is a generalization of the exponential GARCH (EGARCH) model of Nelson (1991). We consider categories for asymmetric effects, which describes the difference among the asymmetric effect of the EGARCH model, the threshold effects indicator function of Glosten, Jagannathan and Runkle (1992), and the negative correlation between the innovations in returns and volatility. The new model is estimated by the efficient importance sampling method of Liesenfeld and Richard (2003), and the finite sample properties of the estimator are investigated using numerical simulations. Four financial time series are used to estimate the alternative asymmetric SV models, with empirical asymmetric effects found to be statistically significant in each case. The empirical results for S&P 500 and Yen/USD returns indicate that the leverage and size effects are significant, supporting the general model. For TOPIX and USD/AUD returns, the size effect is insignificant, favoring the negative correlation between the innovations in returns and volatility. We also consider standardized t distribution for capturing the tail behavior. The results for Yen/USD returns show that the model is correctly specified, while the results for three other data sets suggest there is scope for improvement.

Alternative Asymmetric Stochastic Volatility Models

The stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is a generalization of the exponential GARCH (EGARCH) model of Nelson (1991). We consider categories for asymmetric effects, which describes the difference among the asymmetric effect of the EGARCH model, the threshold effects indicator function of Glosten, Jagannathan and Runkle (1992), and the negative correlation between the innovations in returns and volatility. The new model is estimated by the efficient importance sampling method of Liesenfeld and Richard (2003), and the finite sample properties of the estimator are investigated using numerical simulations. Four financial time series are used to estimate the alternative asymmetric SV models, with empirical asymmetric effects found to be statistically significant in each case. The empirical results for S&P 500 and Yen/USD returns indicate that the leverage and size effects are significant, supporting the general model. For TOPIX and USD/AUD returns, the size effect is insignificant, favoring the negative correlation between the innovations in returns and volatility. We also consider standardized t distribution for capturing the tail behavior. The results for Yen/USD returns show that the model is correctly specified, while the results for three other data sets suggest there is scope for improvement.Stochastic volatility; asymmetric effects; leverage; threshold; indicator function; importance sampling; numerical simulations

Effects of animal’s rumen juice on seed germination of Vicia angustifolia with different seed size

To help understand the effects of grazing on seed germination characteristics of Vicia angustifolia L., we conducted a laboratory germination experiment of V. angustifolia L., which is a main companion species of Leguminosae family in alpine grassland of the Qinghai-Tibetan Plateau, using Yak and Tibetan sheep rumen juices along three seed size categories. Results show that Yak and Tibetan sheep rumen juices significantly restrained germination of seeds for three size categories, decreased seed germination percentage, germination index and prolonged first and mean germination times. Meanwhile, the medium-size seeds presented the maximum geminated percentage, and the larger seeds germinated better than the smaller seeds. Additionally, there were significant interaction effects between rumen juice and seed size on seed germination of V. angustifolia. Our results suggest that grazing pressure of animal feed present have significant negatively effects on seed germination for V. angustifolia with different seed size in alpine area of the Qinghai-Tibetan Plateau.Key words: Vicia angustifolia, rumen juice, seed mass, germination, herbivory