Pricing the Groove: hedonic equation estimates for rare vinyl records

ABSTRACT

This contribution adds to the economic literature on the market value of rarity in markets for cultural collectible goods by studying the price of rare audio recordings (chiefly vinyl) sold on the online marketplace Discogs. Community-based variables serve as proxies for (inverse) rarity and (potential) demand. Results show that the elasticity of price with respect to our measure of inverse rarity (demand) ranges between ?0.120 and ?0.140 (0.150 and 0.160). In addition, effects of hedonic characteristics such as the popularity or collectibility of an artist can be identified. Finally, the study provides evidence for premia for rarity at the top end of the distribution of prices.     

Chained,exact and superlative hedonic price changes: estimates from microdata

Scanner data are used to calculate chained, exact (and superlative) hedonic price indexes for television sets. The data source is available for a wide range of goods, the application providing an example of how this method can be more widely applied. The indexes correspond to constant utility, hedonic cost-of-living indexes. The approach improves on the existing direct method, which takes its estimates directly from the coefficients on time dummies in a hedonic regression. It also improves on the matched model method used by statistical agencies. The differences between actual price changes and exact hedonic quality-adjusted price changes are found to be substantial. Base-period and current-period weighted exact hedonic indexes are similar, thus providing good approximations to a superlative index. Estimates from the direct, dummy variable approach were compared to the superlative indexes. The disparities between the results argue for caution in the use of the direct, dummy variable approach to estimating quality-adjusted price changes.     

Average Derivative Estimation of Hedonic Price Models

Conventional parametric techniques for estimatinghedonic price models require a correct functionalform. In this paper, we side-step this parametricshortcoming by estimating a hedonic price model usingaverage derivative estimation (ADE). Thissemiparametric approach produces robust estimates ofthe marginal effects without assuming a specificfunctional form a priori. In our application ofthe model to a unique data set on Korean home prices,ADE produced estimates consistent with priorexpectations, providing initial evidence that themodel may represent a viable alternative when usingthe hedonic approach.     

Nonparametric neural network modeling of hedonic prices in the housing market

This article addresses the contribution to hedonic modeling of a nonparametric approach based on artificial neural network (ANN) regressions. ANNs provide consistent estimates for the hedonic price of each attribute and permit a number of hypotheses on the hedonic price relationship to be tested nonparametrically. In particular, we exploit results by Stinchcombe and White (Econom Theory 14:295?C324, 1998) in order to carry out misspecification testing in linear and semiloglinear hedonic models. The same approach directly applies to testing misspecification of any parametric specification for the hedonic relationship. A nonparametric significance test for the variables in the hedonic model is also proposed. The test extends the approach developed by Racine (J Bus Econ Stat 15(3):369?C378, 1997) in kernel-based nonparametric testing to ANN-based inference. The finite sample performance of the proposed tests is analyzed through Monte Carlo experiments, and simulation-based algorithms for computation of the null distribution of the tests are proposed. Then, the performance of three classes of regression models??linear, semi-log, and ANNs??applied to hedonic price modeling in a Spanish regional housing market is compared. Our results indicate the presence of nonlinear behavior, as predicted by economic theory, with the ANN-based tests detecting statistically significant evidence of misspecification??both in the linear and the semilog specifications??and ANN regressions providing moderate improvement of predictive performance.     

Econometric analysis of price index for home video cassette recorders in the U.S., 1978-1987

This paper conducts an empirical analysis on the U.S. VCR market using a hedonic approach. The paper finds that quality-adjusted price indices decline at 11-12% per year, with a large annual drop of about 18% from 1982-85. Estimation and data analysis reveal interesting aspects of the evolution of quality and price in the VCR market. As a result of the exclusion of the VCR category until 1986, the paper estimates a bias of 2.4% per year in the CPI electronics subindex.     

A variance equality test of the ICAPM on Philippine stocks: post-Asian financial crisis period

Analysis of the data generated from various residential time-of-day electricity pricing projects often involves estimation of a system of demand equations. Both ad hoc demand models and neoclassical demand models have been estimated, often resulting in considerably different estimates of price elasticities. In this paper, elasticity estimates are presented from each type of demand model using data from the Arizona and North Carolina rate demonstration projects. The relationship between the elasticities generated from ad hoc models and separable neoclassical models is explored and the divergent price elasticity estimates are reconciled.     

What role for human capital in the growth process: new evidence from endogenous latent factor panel quantile regressions

The estimates for the human capital effect in cross‐country growth regressions have been subject of considerable controversy. We argue that human capital is intrinsically a multidimensional construct. We construct human capital measure by combining available alternative proxies via confirmatory factor analysis. Using panel data endogenous quantile regression methods we analyse the whole conditional growth distribution by simultaneously accounting for the potential endogeneity of human capital and country‐specific effects. Our results conform to theoretical expectations and we are able to demonstrate the beneficial effect of both the measurement approach and the endogeneity correction on the derivation of theoretically consistent estimates.     

The role of innovation and quality change in Japanese economic growth

This paper explores the use of time series data to isolate quality change in the Japanese economy using a hedonic procedure. We argue that the traditional approach to hedonic estimation based upon panel data sets of different brands in a given product area is extremely resource intensive and, thus, unlikely to be adopted by official statistical bodies outside of key areas, such as computers. This paper adopts a “top-down” approach to see whether more traditional measures of technical change, such as patents, can be used to separate pure inflation from quality change. If this is possible, it offers a much simpler route to estimate the role of quality change in economic growth and performance. In practice, we extend the analysis not only to include patents, but other forms of intellectual property that might reflect technology and attribute changes, such as designs, utility models and trademarks. We begin by taking a longer-term historical perspective, exploring the development of indigenous inventive capacity in Japan during the early years when R&D data are not available. It is possible to show that the rise in utility models pre-dates the main growth in patenting activity, suggesting the development in more low-level indigenous creative work prior to higher level inventive activity. The principal aim of this paper, however, is to demonstrate that it is possible to develop robust models to explain changes in the producer price index in Japan, which can then be used to re-examine Japanese growth performance over the period from about 1960. If the official Japanese statistical body has fully accounted for quality change in the price indices (i.e. produced fully quality-constant price deflators), then the official estimates of growth will be correct. However, we provide strong evidence that this is not the case. Changes in quality, proxied by the IP variables, are important determinants of prices in Japan over the period 1960 to 1995 as a whole. Indeed, we provide evidence that the true rate of growth of the Japanese economy, taking into account the rate of quality change, is significantly higher than that suggested in official statistics.     

Forecasting the aggregate stock market volatility in a data-rich world

ABSTRACT

In this article, we utilize the basic lasso and elastic net models to revisit the predictive performance of aggregate stock market volatility in a data-rich world. Motivated by the existing literature, we determine several candidate predictors that have 22 technical indicators and 14 macroeconomic and financial variables. Our out-of-sample results reveal several noteworthy findings. First, few macroeconomic and financial variables and most of technical indicators have superior performance relative to the benchmark model. Second, combination forecasts are able to significantly beat the benchmark and some signal predictors Third, the lasso and elastic models with all predictors can generate more accurate forecasts than the benchmark and some other predictors in both the statistical and economic sense. Fourth, the lasso and elastic models exhibit higher forecast accuracy during periods of expansions and recessions. Finally, our findings are robust to several tests, such as different forecasting windows, forecasting models, and forecasting evaluations.     

Estimating Quality‐adjusted Price Changes: Method and Application to VCRs

This paper uses scanner data to generate estimates of quality‐adjusted price changes for video‐recorders. We use hedonic regressions to derive estimates of the changing worth of each quality component. These are then applied to weighted changes in the mix of quality attributes of products to derive estimates of quality‐adjusted price (QAP) changes. The data source used is electronic‐point‐of‐sale (EPOS) scanner data that are available for a wide range of goods. This study provides an example of how such methods can be more widely applied. The estimates of QAP changes correspond to constant‐utility, (hedonic) cost‐of‐living indexes defined in economic theory as the ratio of expenditure functions at constant utility allowing for changing prices and characteristics of goods. This method is proposed as an improvement on the existing direct method , which takes its estimates directly from the coefficients associated with 'time dummies' in a hedonic regression. We finally undertake a matching process, akin to that used by statistical offices, and compare the results. Direct comparisons with RPI estimates and these hedonic approaches are not easy since the approaches use quite different data sets. Our replication of a procedure akin to that used for the RPI on the scanner data set provides insights into sources of potential bias.     

Expert opinion versus actual transaction evidence in the valuation of non-market amenities

Actual property values are overwhelmingly employed as a dependent variable in hedonic pricing models. Yet, assessed property values are generally more readily available than actual sales values and have, in some studies, been used in lieu of market prices. In this study, we compare estimates of different non-market amenity values based on actual transactions and assessed values. We estimate a Seemingly Unrelated Regression (SUR) model with two hedonic price equations, one with actual market values as the dependent variable and the other with assessed property values, and compare the resulting estimates of shadow prices for open space amenities. We also take into account spatial autocorrelation and combine Method of Moment estimates of the spatial parameters in both equations to create our test statistic. The results indicate that we cannot accept the hypothesis that the impacts of open space on property values are the same for actual sales and assessed values. Moreover, we do observe some differences between the distributions of assessed versus sales values, although the difference between the sizes of open space effects measured within the two equations is rather limited. Thus, while this one study is insufficient to enable one to draw definitive conclusions, there remains the possibility that policy makers cannot reliably base decisions on amenity values obtained from a hedonic model using assessed values.     

Using Scanner Data to Estimate Country Price Parities: A Hedonic Regression Approach

This paper uses scanner data from the bar-code readers of retailers to provide estimates of inter-country price parities at the level of the basic heading. The use of such data is appealing given its extensive coverage of transactions, information on weights, prices and characteristics of items at a highly detailed level. The study uses dummy variable hedonic and exact/superlative hedonic index number formulations applied to an inter-country context for both bilateral and multilateral comparisons. Unlike conventional methods, such methods are not confined to matched samples comparisons and thus make use of the entire sample. Their application extends to price survey data using checklists on characteristics. The application is to scanner data on about 1 million transactions for television sets over two months in three countries. It is, to the authors' knowledge, the first such use of scanner data and application of the above hedonic frameworks in this context.     

Hedonic prices and cost/benefit analysis

Hedonic prices have been used to evaluate the willingness to pay for attributes. We reformulate the notion of hedonic price from a composite price on housing to a unit price on traded quantities, in conformity with long run competitive equilibrium theory. This formulation was suggested (but not developed) by Rosen (J. Polit. Econ.82, No. 1 (1974), 34–35). By first characterizing an efficient allocation of consumers to space, we show that hedonic unit prices can be understood as a bid-rent function which supports the efficient allocation. This is despite the fact that the lots over which consumers bid are themselves endogenous. We show that unit hedonic prices reveal preferences in a manner different from composite hedonic expenditures.     

Key market values for bottled wine in an emerging market: product attributes or business strategy?

ABSTRACT

This article focuses on the emerging bottled Chilean red wine market and studies the main determinants of the consumer price of wine sold on the domestic market. A hedonic price function was estimated for a sample of 810 wines using a quantile regression (QR) model. The database contains three variable groups to explain price: objective variables (national, international and vine quality designations), subjective variables (wine score) and business strategies used by wine producers. Results show that some objective variables have a greater impact on price than the wine score (a subjective variable) and business strategies, which vary for each quartile of prices analysed. Finally, this information will allow companies to design and implement marketing strategies to inform the consumer about the importance of some variables in the price of their product.     

The cost of capital,finance and high‐tech investment

Investment is the most volatile component of aggregate demand and it is often considered central to business cycles fluctuations. The responsiveness of business investment to changes in its price is thus crucial to our understanding of economic activity. In spite of the key role played by the user cost of capital in economic analysis, there is little empirical support for the existence of substantial user cost elasticity. However, most of the evidence to date is based on aggregate user cost data, which may have introduced downward biases in the estimated user cost. This paper contributes to the literature by constructing a disaggregated, industry‐specific micro user cost variable and focusing on a special class of firms – the high‐tech firms. To provide a benchmark for the results, the user cost estimates for the high‐tech sector are compared with those for the rest of the manufacturing sector. The results suggest that there is little response of investment to variations in its user cost. The findings also suggest that high‐tech firms’ investment behavior is not, after all, that different from the rest of the manufacturing sector.     

Does clean air matter in developing countries' megacities? A hedonic price analysis of the Jakarta housing market, Indonesia

Despite numerous hedonic studies on the value of clean air in developed countries, the lack of similar studies in less developed countries has raised the question as to whether clean air also matters in developing countries' megacities. As an attempt to fill this gap, we apply a hedonic property value analysis, the method commonly used to infer the value of clean air in developed countries, using the combination of data on housing rental prices and their characteristics from the Indonesian Family Life Survey, and data of the ambient level of six different pollutants in Jakarta, Indonesia. The result indicates that, in the cases of lead, total hydro carbon (THC), and SO₂, air pollutants have a negative association with property value; i.e., housing rental price. The relationship is at 5% level of significance for lead and 10% level for THC and SO₂. This paper estimates that per family value of clean air in Jakarta ranges from US$28 to US$85 per μg/m³.     

Competition and open source with perfect software compatibility

In this paper we study duopolistic competition between closed and open source software. Inspired by recent contributions on open source, we propose a two-stage game with perfect information and product differentiation, in which producers first set software quality and then determine prices (the price is zero for open source programs). We assume perfect software compatibility and model lock-in effects, a network externality component of software quality, and accumulation of experience in software use and implementation. In comparison to the monopolistic benchmark case, we argue that, in a duopoly created by the emergence of an open source program, the proprietary software producer will reduce its selling price if: (i) its network of users is larger than the open source network and its consumers are largely familiar with its program, (ii) it has a small network of unskilled consumers. On the other hand, the price of proprietary software will increase if its users form a large, but poorly-skilled network. Furthermore, we show that, in all of the above cases, the hedonic quality of proprietary software increases. Finally, by modeling experience accumulation processes through difference equations, we show that the ratio between the closed and open source programs’ opportunity costs for software learning and deployment plays a crucial role in shaping market outcomes. If open source software remains too complex and technical for unskilled or time-pressed users, a shared market solution, in which both programs are adopted, is likely to emerge. However, if opportunity costs in learning and understanding open source programs are particularly low, or at least equal to the opportunity costs of a closed-source program, then open source dominance emerges (i.e. markets tip to open source).     

Innovation performance across Europe

The innovation performance of firms is primarily determined by their own innovative activities and the interaction with their innovation-related environment. This environment typically differs among countries. We assess empirically these differences on firms' innovation performance. To that end we first estimate the relationship between an aggregate innovation input measure and an aggregate innovation output measure, thereby explicitly controlling for structural differences between countries. We then consider the extent to which firms located in a particular country perform better or worse than this estimated benchmark performance. The analysis is based on a panel dataset that we have constructed from Eurostat's first and second Community Innovation Survey. In order to control for possible data contamination we employ an outlier-robust estimator. It appears that among the fourteen countries considered Italy, Germany and Ireland offer an environment that facilitates most the transformation of innovation-related inputs into commercial outputs while the environment in Denmark is the least facilitating.     

Economic burden of healthcare-associated infection in US acute care hospitals: societal perspective

Abstract

Background:

Assessing the costs of healthcare-associated infection (HAI) is challenging. Methodological issues abound. Previous estimates have been derived in diverse ways from varied perspectives in different settings with dissimilar data. Results can be confusing. Full societal costs, which are more inclusive than commonly reported direct hospital costs, have never been fully measured or reported.

Objective:

To update, combine, and expand previous cost estimates to determine the annual societal burden of illness (direct medical, non-medical, and indirect costs) arising from HAIs in US acute-care hospitals.

Methods:

The research approach encompassed literature and internet searches; reference identification, selection, and review; then data abstraction, compilation, and analyses to estimate full societal costs. Previously published systemic reviews, surveillance reports, and individual clinical studies, along with newly computed component costs, all contributed to final estimates.

Results:

HAIs in US acute-care hospitals lead to direct and indirect costs totaling $96–$147 billion annually. These results are subject to the same limitations as previous studies from which contributing data were derived.

Conclusion:

The enormous clinical and economic burden of infection places HAIs high on the list of devastating and costly illnesses, such as cancer, heart attack, stroke, and diabetes, thereby mandating further research and greater efforts to contain a pressing healthcare problem.     

Financial impact of a novel pre-eclampsia diagnostic test versus standard practice: a decision-analytic modeling analysis from a UK healthcare payer perspective

Abstract

Objective:

Pre-eclampsia (PE), a leading cause of maternal and perinatal morbidity and mortality, is only detected after symptomatic onset. Early diagnosis may be possible with a new serum test, with resulting clinical and economic benefits versus standard practice. The authors evaluated the financial impact to the UK National Health Service (NHS).

Methods:

A decision-analytic model was developed in which a cohort of 1,000 pregnant women receiving UK obstetric care was simulated. The economic impact of improved sensitivity and specificity of the novel PE test [Roche Diagnostics, Rotkreuz, Switzerland] over current diagnostic practice was modeled. While there is no specific approved diagnostic test to detect PE, physicians are using a combination of tests including blood pressure, proteinuria, Doppler, serum uric acid, etc. The novel PE test constitutes two novel biomarkers Placenta Growth Factor (PlGF) and soluble fms-like tyrosine kinase-1 (sFlt-1) which can be quantitatively analyzed using an automated system widely available in hospitals or laboratories (Elecsys/Cobas, Roche Diagnostics) and measures the levels of PlGF and sFlt-1 growth factors in pregnant women. The analysis assumed administration of the £31.13 test (the equivalent of 52 Swiss Francs [CHF]) after 20 weeks of gestation as an addition to current practice. True-positive and false-negative patients were assumed to develop mild or severe PE, eclampsia, or death. A hybrid research approach was adopted; when available, data for model inputs were obtained from published literature and public databases. Interviews with obstetricians, laboratory managers, and healthcare payers were used to validate model inputs and fill utilization-related data gaps.

Results:

The model estimates that the costs associated with managing a typical pregnancy are £1,781 per patient when the new test is used versus £2,726 with standard practice. This represents savings of £945 per pregnant woman, if the test is used as a supplementary diagnostic tool. The savings are attributed to the new test's improved performance and its ability to better classify the pregnant patients.

Conclusions:

The novel test has the potential to provide substantial cost savings for NHS. Even when the novel test's cost is added to the current cost of care, the benefits exceed the additional cost, driven by the test's ability to reduce the rates of false-positive and false-negative diagnoses compared to current standard of care. Potential study limitations include the use of a pooled average of the individual sensitivities and specificities of currently used tests since no data were available on combination testing, the reliance on clinical trial data versus actual practice, and the use of clinical expert opinion when published data were unavailable.