Shadow prices of environmental outputs and production efficiency of household-level paper recycling units in Vietnam

The production efficiency and shadow prices of three environmental outputs (BOD, COD, and SS) of 63 household-level paper-recycling units, from a recycling craft village in Vietnam, are assessed A two-stage procedure, linear programming and stochastic estimation, is used to estimate output distance function. Social capital as a production factor and environmental outputs are included in the output distance function. Results indicate that production efficiencies could potentially be improved by 28%. There is a substantial variation in the shadow prices of environmental outputs among the production units of different types of paper products. Furthermore, the average shadow prices of the three environmental outputs are all positive. This indicates a potential for improving environmental quality though introducing pollution-prevention methods to paper-recycling production processes in Vietnam (e.g., recirculation of wastewater), and suggests that it may be inappropriate to restrict the shadow prices of environmental outputs to be non-positive for the analysis of some production processes.     

The out-of-sample forecasting performance of nonlinear models of regional housing prices in the US

This article provides out-of-sample forecasts of linear and nonlinear models of US and four Census subregions’ housing prices. The forecasts include the traditional point forecasts, but also include interval and density forecasts, of the housing price distributions. The nonlinear smooth-transition autoregressive model outperforms the linear autoregressive model in point forecasts at longer horizons, but the linear autoregressive and nonlinear smooth-transition autoregressive models perform equally at short horizons. In addition, we generally do not find major differences in performance for the interval and density forecasts between the linear and nonlinear models. Finally, in a dynamic 25-step ex-ante and interval forecasting design, we, once again, do not find major differences between the linear and nonlinear models. In sum, we conclude that when forecasting regional housing prices in the United States, generally the additional costs associated with nonlinear forecasts outweigh the benefits for forecasts only a few months into the future.     

Shadow directional distance functions with bads: GMM estimation of optimal directions and efficiencies

Because of its greater flexibility, the directional distance function (DDF) has been employed with increasing frequency to estimate multiple-input and multiple-output production, where inputs and outputs can be good or bad. However, typically researchers make three restrictive assumptions. First, they assume a direction of movement of firm production toward the frontier. Second, they assume that actual quantities of inputs and outputs are allocatively or price efficient. Third, they assume exogeneity of all inputs and all outputs, except for the normalized one. The first contribution of this paper is to include parameters to estimate optimal directions which correspond to the firm’s profit-maximizing (PM) position. The second contribution is to generalize the DDF to a shadow-quantity DDF. This entails adding distortion parameters to each input and output quantity of the DDF, creating shadow quantities. To estimate the shadow quantities and the structural parameters, we form the shadow DDF system, which includes the shadow DDF and all the first-order price equations from the shadow-PM problem. These include prices for bad inputs and bad outputs, where we approximate their missing prices for use in their first-order price equations. The third contribution is that we estimate the shadow DDF system using a Generalized Method of Moments approach, where all variables are potentially endogenous. This approach is simpler than the Bayesian one employed in Atkinson et al. (Estimating efficient production with bad inputs and outputs using latent prices and optimal directions. Working paper, University of Georgia, Athens, 2016), which estimated shadow prices and optimal directions. Using the same data set, both sets of results are qualitatively very similar, although they differ somewhat quantitatively.     

Evaluating the carbon-macroeconomy relationship: Evidence from threshold vector error-correction and Markov-switching VAR models

This paper studies the nonlinear adjustment between industrial production and carbon prices – coined as ‘the carbon-macroeconomy relationship’ – in the EU 27. We model carbon price returns and industrial production as nonlinear and state-dependent, with dynamics depending on the sign and magnitude of past realization of returns and the growth of industrial production. Our findings show that (i) macroeconomic activity is likely to affect carbon prices with a lag, due to the specific institutional constraints of this environmental market; (ii) the joint dynamics of industrial production and carbon prices seem adequately captured by two-regime threshold vector error-correction and two-regime Markov-switching VAR models compared to linear models as main competitors. The regime-switching models proposed are profoundly checked for their economic content and statistical congruency, and are found to provide a sound statistical framework for a comprehensive analysis of the carbon-macroeconomy relationship.     

Housing market cycles in large urban areas

This paper examines the behaviour of house prices in large metropolitan areas. Using a sample of metropolises it is shown that real estate prices are largely nonlinear. It is found that dynamic asymmetries in the housing market cycle can well be modelled using a logistic smooth transition model (LSTAR). Further, it is found that the LSTAR specification has better forecasting properties with respect to other linear and nonlinear models.     

Discount rates and shadow prices for public investment

This paper extends the Harberger–Sandmo–Drèze model for public discount rates to a many-good economy. It derives a formula for discount rates which are specific to each public enterprise or agency and used by them to discount future outputs and inputs evaluated at market prices. Such an approach is shown to be more efficient than that of simply using a single rate for all public projects. It is also more practical than asking each public firm to use second-best shadow prices in their analyses of investment projects.The general results are first provided; then, simple cases are considered and numerical examples presented to help interpret our formula and analyse its main determinants.     

Jointness in production and farmers' willingness to supply non-marketed ecosystem services

This paper highlights how farmers' willingness to supply non-marketed ecosystem services (ES) is influenced by whether or not the non-marketed ES are produced jointly with agricultural products. When marketed products and non-marketed ES share some production inputs the production relationships between the two may be complementary, competitive or substitutive. Using a cost minimization framework, it is shown how complementary relationships lead to costless voluntary provision of non-marketed ES (typically the case for ES that are supportive of provisioning ES for marketed farm products). It is also shown how competitive production relationships lead to provision of non-marketed ES at lower cost than when non-marketed ES are direct substitutes for farm products or are produced outside of agriculture. The paper closes by showing how the minimum willingness to accept (WTA) payment for ES that are complementary/competitive is less than or equal to the minimum WTA for the same ES produced in substitute or independent production relationships.     

Non-marketed options, non-existence of equilibria, and non-linear prices

This paper presents a surprising example that shows that the lattice theoretic properties in Mas-Colell's (1986) seminal work are relevant to the existence of equilibrium even when the commodity space is finite dimensional.The example is a two-period securities model with a three-dimensional portfolio space and two traders. The paper identifies a non-marketed call option that fails to have a minimum cost super-replicating portfolio. Using this option, we construct an economy that satisfies all of Mas-Colell's assumptions, except that the three-dimensional commodity space is not a vector lattice. In this economy, there is no Walrasian equilibrium and the second theorem of welfare economics fails.Our example has important finite- as well as infinite-dimensional implications. It is also an example of a “well behaved” economy in which optimal allocations that are not supported by linear Walrasian prices are decentralized by the non-linear prices studied in Aliprantis-Tourky-Yannelis (2001).     

Ascending price Vickrey auctions

We show that an ascending price auction for multiple units of a homogeneous object proposed by Ausubel (i) raises prices for packages until they reach those nonlinear and non-anonymous market clearing prices at which bidders get their marginal products and (ii) the auction is a primal–dual algorithm applied to an appropriate linear programming formulation in which the dual solution yields those same market clearing prices. We emphasize the similarities with efficient incentive compatible ascending price auctions to implement Vickrey payments when there is a single object or when objects are heterogeneous but each buyer does not desire more than one unit. A potential benefit of these common threads is that it helps to establish the principles upon which Vickrey payments may be implemented through decentralized, incentive compatible procedures.     

Technical substitution of production factors through shadow pricing of factors

In underdeveloped countries, the market prices of factors do not reflect their economic opportunity cost, because of various market imperfections, state regulations, and population growth. Therefore, it is necessary that shadow prices of factors, instead of market prices of factors, should be used in the evaluation and selection of projects. Three alternative approaches to derive shadow prices have been outlined along with their shortcomings.     

Regime switching and the (in)stability of the price–rent relationship: evidence from the US

Present value models of house prices assert that in the absence of self-fulfilling bubbles, a house price is equal to the present discount value of all future rents, which implies a linear relationship between house price and rent, and hence a stable price-to-rent ratio. Using a Markov switching error correction model, we re-examine this relationship in the US housing market and find two distinctive regimes: one with a long-run relation between house price and rent predicted by the present value models and the other in which the relation is nonlinear. Furthermore, we find evidence that deviations of house prices from the present value models’ predictions are caused by the overreaction of house prices to movements in rents rather than speculative bubbles attributable to extraneous factors.     

Evaluating market efficiency without price data: the Swedish market for wood fuel

The overall objective of this paper is to analyse the price development and price formation for wood fuel used by the Swedish district heating sector. According to Lönner et al., there is a significant potential for increasing the use of wood fuel in Sweden, at a fairly moderate cost. The basic question raised in this paper is then why this potential is not realized. Specifically, a methodology is proposed for testing whether the reason is that market imperfections are present. As a first step the shape of the technology in the Swedish district heating sector is estimated for the period 1989 to 1996. In the second step the estimated technology and the assumption of cost-minimizing firms are combined to calculate shadow prices, i.e. marginal valuation of wood fuel in this sector. If the average shadow price significantly deviates from the average observed price one may conclude that this market is functioning inefficiently due to imperfections. According to constructed bootstrap confidence intervals this difference is significant only for three out of eight years, implying that the quantities of wood fuel traded are too small. For the other years the difference is not significant, implying that one cannot, on statistical grounds, reject the efficient market hypothesis for all years.     

Bitcoin price and its marginal cost of production: support for a fundamental value

This study back-tests a marginal cost of production model proposed to value the digital currency Bitcoin. Results from both conventional regression and vector autoregression (VAR) models show that the marginal cost of production plays an important role in explaining Bitcoin prices, challenging recent allegations that Bitcoins are essentially worthless. Even with markets pricing Bitcoin in the thousands of dollars each, the valuation model seems robust. The data show that a price bubble that began in the Fall of 2017 resolved itself in early 2018, converging with the marginal cost model. This suggests that while bubbles may appear in the Bitcoin market, prices will tend to this bound and not collapse to zero.     

Shadow pricing of labour and capital in an economy with unemployed labour

This paper derives the shadow prices of labour and capital to be used in the public sector in a situation of unemployment. The setting considered is that of a three-good, two-period general equilibrium model. Then shadow prices are compared to their corresponding market prices and shown to closely depend on own and cross-elasticities of supply and demand for labour and investment. In the first part, a rigid wage rate is the sole source of distortion; then, a tax on capital income is introduced so that our formula for the social rate of discount can be contrasted with that of Harberger, Sandmo and Drèze.     

Land price diffusion across borders – the case of Germany

ABSTRACT

Land market regulations are often justified by the assumption that activities of foreign and non-agricultural investors drive up prices in domestic land markets. However, empirical knowledge about the dynamics of agricultural land prices across borders is sparse. Using the German reunification as a natural experiment, we study the effect of the former inner German border on the dynamics of agricultural land prices in East and West Germany. We apply a land price diffusion model with an error correction specification to analyse spatial agricultural land markets. A novel feature of our model is its ability to distinguish price diffusion within states and across state borders. We provide evidence for a persistent border effect given that the fraction of spatially integrated counties is larger within states than across the former border. Moreover, we observe non-significant error correction terms for many counties along the former border. From a policy perspective, it is striking to realize that even 25 years after German reunification, pronounced land price differences persist. It is quite likely that price diffusion through existing borders within the EU would take even more time given language barriers, different institutional frameworks, and information asymmetries between domestic and foreign market participants.     

国家政策对农产品价格波动的影响分析——以棉花为例

2003年以来,我国一些主要农产品开始减产,价格开始逐渐回升,到2007年快速上涨,引发全国物价总水平不断攀升。以棉花为例,阐述了农产品价格形成机制的变迁,分析了国家政策对农产品价格波动的影响,在此基础上,提出了稳定农产品价格的对策。     

Jumps and volatility dynamics in agricultural commodity spot prices

The spot commodities market exhibits both extreme volatility and price spikes, which lead to heavy-tailed distributions of price change and autocorrelation. This article uses various Lévy jump models to capture these features in a panel of agricultural commodities observed between January 1990 and February 2014. The results show that Levy jump models outperform the continuous Gaussian model. Our results prove that assuming a constant volatility or even a deterministic volatility and drift structure of agricultural commodity spot prices is not realistic and is less efficient than the stochastic assumption. The findings demonstrate an interesting correlation between volatility and jumps for a given commodity i, but no relationship between the volatility of commodity i and the probability of jumps of commodity j.     

Special offers and clustering under symmetric monopoly

A monopolist offerings variants on a Salop circle is analyzed with respect to his choice of product variants and prices. Although we assume a uniform distribution of tastes, the profit-maximizing pattern is not equidistant in variants and prices are not the same for all variants.Instead, under fairly general circumstances, there exists at least one cheap variant (special offer) around which the more expensive ones are clustered. This result depends on the assumption that the market size is not fixed as in most other models of this sort, but depends on prices in a straightforward manner.     

Measuring environmental efficiency of industry: a case study of thermal power generation in India

Technical and environmental efficiency of some coal-fired thermal power plants in India is estimated using a methodology that accounts for firm’s efforts to increase the production of good output and reduce pollution with the given resources and technology. The methodology used is directional output distance function. Estimates of firm-specific shadow prices of pollutants (bad outputs), and elasticity of substitution between good and bad outputs are also obtained. The technical and environmental inefficiency of a representative firm is estimated as 0.06 implying that the thermal power generating industry in Andhra Pradesh state of India could increase production of electricity by 6/ while decreasing generation of pollution by 6%. This result shows that there are incentives or win–win opportunities for the firms to voluntarily comply with the environmental regulation. It is found that there is a significant variation in marginal cost of pollution abatement or shadow prices of bad outputs across the firms and an increasing marginal cost of pollution abatement with respect to pollution reduction by the firms. This result calls for the use of economic instruments like pollution taxes instead of command and control regulation used currently in India to reduce air pollution.

Financial Market Data Versus Accounting Data: Which Better Explains Stock Returns?

This paper presents the comparison of how financial market and accounting data affect stock prices and returns. The goal was to ascertain whether financial information or accounting data dominate in evaluating stock prices. Most valuation techniques used by firms are based on models using either accounting variables (earnings, book value, cash flows, research and development expenses) or financial market data (e.g. beta, market value, interest). The answer is of great importance for valuators and investors as it will help them focus on the most important variables and make better valuations and choices. This answer is also important for accounting standard setters as the preferred method will serve as an indicator for the quality of financial statements and their importance to users. The paper contributes to the existing literature in the fields of value relevance of accounting information and firm valuation and accounting standards (e.g. International Financial Reporting Standards, United States General Accepted Accounting Principles). To answer this question, share prices were estimated based on financial data using the capital asset pricing model and for accounting data, using Ohlson’s model. The results were tested for both methodologies by comparing estimated share prices with actual ones. The greater the correlation between the two variables the better the explanatory power of the model. The focus was on S&P 500 firms for the period 2002–2017.