A Time Series Analysis of U.K. Lottery Sales: Long and Short Run Price Elasticities

This paper estimates the long- and short-run elasticities for Lotto. It is particularly concerned with the dynamic response to price variations since, for some goods, this has sometimes been used to infer the presence of addiction. The price elasticity is identified through variation in the expected value of a Lotto ticket induced by rollovers whose high frequency results in surprisingly high variation in the expected value of holding a ticket. Unit root tests are applied to the series in order to identify their time series properties and to avoid a spurious regression problem. The series are found to be stationary. We apply instrumental variables to account for the endogeneity which arises due to correlation between the expected value and the dependent sales variable. The estimated long-run elasticity exceeds the short-run elasticity and this supports the hypothesis that there is an element of addictive behaviour in sales. The Lottery is regulated and the regulator's objective is to maximize sales. Our estimated long-run price elasticity of demand is inconsistent with revenue maximization and we find that greater revenue for the 'good causes' could be raised from the game if a smaller proportion of sales revenue were allocated to them.     

Option value and the price of teardown properties

The introduction of uncertainty over the future price of structural capital into a model of teardowns implies a value to delaying the demolition vs. preservation decision, and that the market price of a redeveloped property may increase with its quantity of structural capital. Using data from an active teardown market, we test the model’s prediction that hedonic price function coefficients depend on the expected time between sale and demolition. As predicted, structural variables have significant effects on the sales prices of both teardown and non-teardown properties, and the effects are generally much larger the lower the estimated teardown probability.     

Dynamics between patent latent variables and patent price

This paper focuses on studying the relationship between patent latent variables and patent price. From the existing literature, seven patent latent variables, namely age, generality, originality, foreign filings, technology field, forward citations, and backward citations were identified as having an influence on patent value. We used Ocean Tomo's patent auction price data in this study. We transformed the price and the predictor variables (excluding the dummy variables) to its logarithmic value. The OLS estimates revealed that forward citations and foreign filings were positively correlated to price. Both the variables jointly explained 14.79% of the variance in patent pricing. We did not find sufficient evidence to come up with any definite conclusions on the relationship between price and the variables such as age, technology field, generality, backward citations and originality. The Heckman two-stage sample selection model was used to test for selection bias.     

房价影响因素的实证分析——以青岛市为例

运用SPSS软件,以人口、人均GDP、住房销售面积和房地产开发投资为自变量,采用2000～2009年10年的数据,建立了多元线性回归模型,对青岛市房价这一因变量进行了模拟分析。模型通过各种检验,得出了影响青岛市住房价格最重要的因素是市区人口这一结论,说明青岛市有效的需求增大,是抬高住房价格十分重要的因素,这在一定层面上说明了青岛的住宅市场的价格是比较正常的价格。     

Illicit drug use among arrestees, prices and policy

Prior studies, by relying on nationally representative surveys, have overlooked the important fact that use of addictive substances is not uniformly distributed; subgroups of hardcore users account for most of the drug consumption. This study employs the Arrestee Drug Abuse Monitoring system to analyze the demand for cocaine and heroin by urban arrestees, employing objective indicators of use based on urinalysis. The data are repeated city cross sections, and panel data methodology is employed to account for endogeneity. Cocaine and heroin prices have a negative effect on the probability of use even among this group of heavy users. Results indicate that subjective, self-reported measures of participation are likely to be under-reported, which may impart bias to estimates of the price elasticity. The own-price cocaine participation elasticity is about −0.15, and the own-price heroin participation elasticity is about −0.10 for arrestees. This contemporaneous elasticity understates the full effect, and the long-run price elasticity is about twice the magnitude. The magnitude of the price response is substantially smaller relative to the estimates in the prior literature, and calculations suggest that further enforcement and interdiction-driven increases in drug prices may not be cost-effective.     

Incentive pay and rent in oligopoly

Our purpose is to examine strategic delegation in nonlinear Cournot oligopoly. The findings generalize earlier results and show that managerial contracts reward sales under the condition of a fixed input price. Alternatively, under a variable input price, owners might punish sales even when goods are strategic substitutes. We conclude that optimal strategic motivation depends critically on the input price. For example, motivation that supports positive owner profit under a fixed input price nullifies owner-profit if an upstream monopolist with convex costs sets the input price. In a vertical relationship between a duopoly and an upstream monopolist, strategic delegation punishes sales.     

Contracting on the Stock Price and Forward-Looking Performance Measures

Abstract

We examine the use of earnings, forward-looking performance measures and stock prices in managerial compensation. When the firm's owner and its manager have identical time preferences, the stock price is not useful for motivating the manager, as it is a noisy aggregation of a forward-looking measure and future earnings. In contrast, when the owner and the manager have conflicting time preferences, the noisy stock price is useful for contracting. If the manager has no access to banking and cannot trade the firm's shares, the timeliness of the stock price dominates the extra risk imposed by its noise. At the same time, forward-looking performance measures (such as customer satisfaction) can induce a desirable allocation of management effort between the short term and long term more efficiently than the stock price can. Forward-looking performance measures and the stock price are thus not direct substitutes in rewarding farsighted effort.     

Return to education in Finland

This study presents estimates of the return to education in Finland using an individual-level data set that also includes ability measures and information on family background. It is found that ability test scores have a strong effect on the choice of education and on subsequent earnings. Estimating the return to education with no information on ability leads to an upward bias in the estimates. However, this bias is more than offset by a downward bias caused by endogeneity or measurement error. Instrumental variables estimates that utilize family background variables as instruments produce estimates of the return to schooling that are approximately 60% higher than the least squares estimates.     

Editorial

This paper reports the results of 16 market experiments designed to produce measures of the effects of nonresidential land uses on the prices of nearby dwellings. Each experiment consists of a sample of home sales in a homogeneous neighborhood located near a single nonresidential land use, e.g., industry, commercial, high-density dwellings, and highways. The data consist of price, physical characteristics of the dwelling, distance from the nonresidential use, and the date of sale for each transaction. Hedonic price indices are estimated and the significance of the distance effects assessed. No systematic relationship between nonresidential land use per se and housing prices is found.     

Estimating house price appreciation: A comparison of methods

Several parametric and nonparametric methods have been advanced over the years for estimating house price appreciation. This paper compares five of these methods in terms of predictive accuracy, using data from Montgomery County, Pennsylvania. The methods are evaluated on the basis of the mean squared prediction error and the mean absolute prediction error. A statistic developed by Diebold and Mariano is used to determine whether differences in prediction errors are statistically significant. We use the same statistic to determine the effect of sample size on the accuracy of the predictions. In general, parametric methods of estimation produce more accurate estimates of house price appreciation than nonparametric methods. And when the mean absolute prediction error is used as the criterion of accuracy, the repeat sales method produces the most accurate estimate among the parametric methods we tested. Finally, of the five methods we tested, the accuracy of the repeat sales method is least diminished by a reduction in sample size.     

Three Factors to Signal Non‐Response Bias With Applications to Categorical Auxiliary Variables

Non‐response causes bias in survey estimates. The unknown bias can be reduced, for example as in this paper by the use of a calibration estimator built on powerful auxiliary information. Still, some bias will always remain. A bias reduction indicator is proposed and expressed as a product of three factors reflecting familiar statistical ideas. These factors provide a useful perspective on the components that constitute non‐response bias in estimates. To illustrate the indicator, we focus on the important case with information defined by one or more categorical auxiliary variables, each expressed by two or more properties or traits. Together, the auxiliary variables may represent a large number of traits, more or less important for bias reduction. An examination of the three factors of the bias reduction indicator brings the insight that the ultimate auxiliary vector for calibration need not or should not contain all available traits; some are unimportant or detrimental to bias reduction. The question becomes one of selection of traits, not of complete auxiliary variables. Empirical examples are given, and a stepwise procedure for selecting important traits is proposed.     

The inconsistency of common scale estimators when output prices are unobserved and endogenous

This paper explores the inconsistency of common scale estimators when output is proxied by deflated sales, based on a common output deflator across firms. The problem arises when firms operate in an imperfectly competitive environment and prices differ between them. In particular, we show that this problem reveals itself as a downward bias in the scale estimates obtained from production function regressions, under a variety of assumptions about the pattern of technology, demand and factor price shocks. The result also holds for scale estimates obtained from cost functions. The analysis is carried one step further by adding a model of product demand. Within this augmented model we examine the probability limit of the scale estimate obtained from an ordinary production function regression. This analysis reveals that the OLS estimate will be biased towards a value below one, and how this bias is affected by the magnitude of the parameters and the amount of variation in the various shocks. We have included an empirical section which illustrates the issues. The empirical analysis presents a tentative approach to solve the problem discussed in the theoretical part of this paper.     

A dymimic model of housing price determination

This paper presents and estimates a model of the resale housing market. The data are a cross-section of monthly time series obtained from the multiple-listing service for a suburb of San Diego. The model is specified and estimated as a dynamic multiple indicator multiple cause system of equations where the capitalization rate is taken to be an unobservable time series to be estimated jointly with the unknown parameters. These are estimated by maximum likelihood using an EM algorithm based upon Kalman filtering and smoothing.The specification of the model features hedonic equations for each house sale and a dynamic equation for the capitalization rate which is constrained to make the expectation of prices equal the present value of the net returns to home ownership whenever the economic variables stabilize at steady state values. Out of steady state, the capitalization rate slowly adapts to new information.The model attributes a large portion of housing price increases of the 1970's to a fall in the capitalization rate which in turn was driven by rental inflation, tax rates and mortgage rates. Post-sample simulations indicate an initial flattening of housing inflation rates and later a fall brought on by the increase in steady state capitalization rates. In-sample simulations show that although both Proposition 13 and the inflation induced rise in the marginal income tax rates provided partial explanations for the fall in capitalization rates, the single most important factor was the acceleration in price of housing services which interacted with the tax treatment of home ownership to produce an amazing 18% average annual rate of price increase over the last seven years of the 1970's.     

The challenges of using ranks to estimate sales

Researchers have frequently used data on product ranks to estimate nonpublic sales quantities, believing that there is a power-law-induced linear relationship between logged sales ranks and logged sales. Using essentially complete data on book sales, the most commonly used product in this literature, we find that the (double-logged) relationship between sales ranks and quantity sold is not linear, but robustly concave. We demonstrate that this concavity is likely to cause very poor sales predictions in many instances. We provide two concrete examples where applying this linear method to the concave relationship has led to serious errors in sales estimates. First, in the claim that the Internet's greater product variety in books has a large positive impact on social welfare, and second, in a claim about relative sales levels in top 20 and top 50 music “charts.” We also explore the use of nonlinear specifications as an alternative method to predict sales from ranks and find a simple specification that provides much better sales estimates. Finally, we examine the possibility that a particular type of biased sample might allow reasonable linear estimates of industry sales and conclude that it is possible but quite unlikely.     

On the need to compensate the compensating variation in CGE modeling

The message of this research is that in the standard calibrated setting of Computational General Equilibrium (CGE) models, the welfare measures typically used to compare benchmark with counterfactuals are numéraire dependent. This evaluation bias affects the compensating variation and the Konüs index of cost of living. We show that the equivalent variation is neutral regarding the choice of value units in calibrated models but would be affected as well in uncalibrated CGE models. We illustrate with a simple example and propose an even simpler theoretical solution to overcome these biases; all that is required to have correct welfare estimates is to compensate normalizing with a suitable price index. This type of correction is necessary to overcome the sometimes blind implementation of welfare measures in numerical general equilibrium analysis. We show that the induced quantitative errors may be substantial providing biased welfare estimates and misleading results.     

An analysis of stock market transactions data

Many studies have argued against the strict form of the efficient markets hypothesis (EMH) by concluding that a lagged relationship exists between volume and the absolute value of a price change. These studies have denied a priori the possibility of a contemporaneous relationship. If a simultaneous relationship exists then least squares with only lagged variables suffers from omitted variable bias, and least squares with contemporaneous variables may suffer from simultaneous equations bias. Investigating these possibilities, this study demonstrates that simultaneity exists and that previous findings of a lagged relationship between the variables are therefore due to specification error. System estimation techniques suggest that the price-volume relationship is recursive, with the absolute value of a price change causing volume contemporaneously, but not conversely.     

Venture Capital Investments in Europe and Portfolio Firms' Economic Performance: Independent Versus Corporate Investors

Using a new European Commission‐sponsored longitudinal dataset—the VICO dataset—we assess the impact of independent (IVC) and corporate venture capital (CVC) investments on the economic performance of European high‐tech entrepreneurial firms during the period 1992–2010. After controlling for potential sources of endogeneity and selection bias, our results indicate that both IVC and CVC investments boost portfolio firms' economic performance. These effects are mostly due to an increase in real sales value. Moreover, the dynamics of the impact of VC investments on firms’ overall economic performance and its components—real sales value, real fixed assets, and real labor costs—differs depending on the type of investor. Finally, we do not detect any impact related to the syndication of investments by both IVC and CVC investors.     

Two-step estimation of panel data models with censored endogenous variables and selection bias

This paper presents some two-step estimators for a wide range of parametric panel data models with censored endogenous variables and sample selection bias. Our approach is to derive estimates of the unobserved heterogeneity responsible for the endogeneity/selection bias to include as additional explanatory variables in the primary equation. These are obtained through a decomposition of the reduced form residuals. The panel nature of the data allows adjustment, and testing, for two forms of endogeneity and/or sample selection bias. Furthermore, it incorporates roles for dynamics and state dependence in the reduced form. Finally, we provide an empirical illustration which features our procedure and highlights the ability to test several of the underlying assumptions.     

The reliability of self-reported home values in a developing country context

This paper provides an analysis, in the context of a developing country, of the reliability of homeowners’ estimates of the value of their houses, as obtained through a household survey. We show that non-response to the home value question by the owner is uncorrelated with the appraised value of the house and other demographic characteristics of the respondent. We also document that homeowners with long tenure largely overestimate the value of their home. Moreover, both the bias and the lack of precision in homeowners’ estimates are correlated with tenure, but not with socioeconomic characteristics. However, we also show that self-reported home values from short-tenure homeowners can be used to obtain unbiased and precise estimates of the average house value at the census tract level.     

The elasticity of substitution for land: The effects of measurement errors

The explanatory variable used in most previous studies of land-nonland substitution, assessed or appraised land value, is subject to considerable measurement error. There is evidence that this biases the substitution elasticity from a true value of unity to a measured value in the 0.5 to 0.8 range. An hedonic method of measuring land value is proposed and applied to the Chicago residential sales data developed by Berry and Bednarz. Substitution elasticities are estimated within a CES framework from the two measures of land value; after correction for a vintage effect, appraised land value indicates that the elasticity is 0.57 whereas the hedonic measure of land values supports a unitary substitution elasticity. Therefore, the errors-in-variables hypothesis is confirmed and the use of a Cobb- Douglas production function is suggested.