社会政策对人口趋势影响的检验与评估

使用计量经济学中的时间序列模型 ,对我国改革政策对流动人口增长和对计划生育政策对生育率下降作用的显著性进行了检验。再次证实了社会政策对我国人口趋势的显著影响 ,同时对我国生育率的下降用模型分离了计划生育和社会经济发展的独立作用 ,估算了计划生育政策的实行对总和生育率下降、出生人数减少以及总人口增长的量化影响。     

Spatial Interaction,Spatial Multipliers and Hospital Competition

The hospital competition literature shows that estimates of the effect of local market structure (concentration) on pricing (competition) are sensitive to geographic market definition. Our spatial lag model approach effects smoothing of the explanatory variables across the discrete market boundaries, resulting in robust estimates of the impact of market structure on hospital pricing, which can be used to estimate the full effect of changes in prices inclusive of spillovers that cascade through the neighboring hospital markets. The full amount, generated by the spatial multiplier effect, is a robust estimate of the impacts of market factors on hospital competition. We contrast ordinary least squares and spatial lag estimates to demonstrate the importance of robust estimation in analysis of hospital market competition. In markets where concentration is relatively high before a proposed merger, we demonstrate that Ordinary Least Squares (OLS) can lead to the wrong policy conclusion while the more conservative lag estimates do not.     

The Information Content of Model‐Free Implied Volatility

This study examines the information content of model‐free implied volatility (MFIV) estimates with respect to the options and futures markets in Hong Kong. In this study, the volatility forecasting performance of MFIV is compared, using different prediction horizons, to IV estimates based on Black's futures option pricing model (BIV) and time‐series forecasts based on historical volatility (TS‐HV). The results show that the BIV prediction is unbiased for different horizon forecasts. MFIV outperforms TS‐HV forecasts and, most importantly, BIV subsumes the information content of both MFIV and TS‐HV forecasts. The results are largely maintained for next‐day forecasts but the forecasting quality of the two IV measures declines as expiration day approaches. The information contents of MFIV and TS‐HV forecasts are complementary. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 32:792‐806, 2012     

Solving and Testing for Regressor-Error (in)Dependence When no Instrumental Variables are Available: With New Evidence for the Effect of Education on Income

This paper has two main contributions. Firstly, we introduce a new approach, the latent instrumental variables (LIV) method, to estimate regression coefficients consistently in a simple linear regression model where regressor-error correlations (endogeneity) are likely to be present. The LIV method utilizes a discrete latent variable model that accounts for dependencies between regressors and the error term. As a result, additional ‘valid’ observed instrumental variables are not required. Furthermore, we propose a specification test based on Hausman (1978) to test for these regressor-error correlations. A simulation study demonstrates that the LIV method yields consistent estimates and the proposed test-statistic has reasonable power over a wide range of regressor-error correlations and several distributions of the instruments. Secondly, the LIV method is used to re-visit the relationship between education and income based on previously published data. Data from three studies are re-analyzed. We examine the effect of education on income, where the variable ‘education’ is potentially endogenous due to omitted ‘ability’ or other causes. In all three applications, we find an upward bias in the OLS estimates of approximately 7%. Our conclusions agree closely with recent results obtained in studies with twins that find an upward bias in OLS of about 10% (Card, 1999). We also show that for each of the three datasets the classical IV estimates for the return to education point to biases in OLS that are not consistent in terms of size and magnitude. Our conclusion is that LIV estimates are preferable to the classical IV estimates in understanding the effects of education on income. JEL Classification: C12, C13, C21, J3, M3     

Heterogeneous Firms,Globalisation and the Distance Puzzle

Despite the strong pace of globalisation, the distance effect on trade is persistent or even growing over time (Disdier and Head, 2008). To solve this distance puzzle, we use the recently developed gravity equation estimator from Helpman et al. (2008) (HMR henceforth). Using three different data sets, we find that the distance coefficient increases over time when ordinary least squares (OLS) is used, while the non‐linear estimation of HMR leads to a decline in the distance coefficient over time. The distance puzzle, thus, arises from a growing bias of OLS estimates. The latter is explained by an increase in the importance of the bias from omitting the number of heterogeneous exporting firms relative to the bias from omitting zero trade flows. Furthermore, we show that including zero trade flows cannot solve the distance puzzle when using HMR. The HMR estimates are strongly correlated with the time pattern in freight costs reported by Hummels (2007).     

Predicting default probabilities and implementing trading strategies for emerging markets bond portfolios

In this paper, we address two main issues: the computation of default probability implicit in emerging markets bond prices and the impact on portfolio risks and returns of expected changes in default probability. Using a reduced-form model, weekly estimates of default probabilities for U.S. Dollar denominated Global bonds of 12 emerging markets are extrapolated for the sample period 1997–2001. The estimation of a logit type econometric model shows that weekly changes of the default probabilities can be explained by means of some capital markets factors. Recursively estimating the logit model using rolling windows of data, out-of-sample forecasts for the dynamics of default probabilities are generated and used to form portfolios of bonds. The practical application provides interesting results, both in terms of testing the ability of a naive trading strategy based on model forecasts to outperform a “customized benchmark”, and in terms of the model ability to actively manage the portfolio risk (evaluated in terms of VaR) with respect to a constant proportion allocation.     

Adoption rate forecasts and rollout strategies

Long-term broadband penetration forecasts for Western Europe are presented. The broadband penetration forecasts are adjusted according to the broadband coverage. The adjusted forecasts are defined as adoption rate forecasts. These forecasts are used as input to the techno-economic calculations to examine broadband roll out in the different access area types. The paper documents the profitability of broadband rollouts in sparsely populated areas and estimates the limits for having monopoly areas as a function of given characteristics. The identified monopoly areas will of course contribute to higher broadband coverage because the profitability in these small areas will be better than earlier expected because of none competition.     

A note on the superiority of the OLS hedge ratio

Suppose that spot and futures prices are generated from an error‐correction model. This note demonstrates that, although the OLS model is misspecified, it provides a hedge ratio that usually outperforms the hedge ratio derived from the correct error‐correction model. The opposite result is possible only when the postsample incurs a major structural change from the estimation sample. ©2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:1121–1126, 2005     

A further note on the optimality of the OLS hedge strategy

This note considers the hedging effectiveness of a dynamic hedge strategy as compared to the conventional OLS strategy. The conditions for the superiority of the OLS strategy are identified. It is argued that these conditions are frequently satisfied and therefore one expects to find the dominance of the OLS strategy over any dynamic strategy in the empirical work. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:308–311, 2008     

A stochastic programming model to analyze ordinal preference data

Many marketing situations require analysis of ordinal preference data. Existing analysis methods include OLS, variations of the logit model and methods such as LINMAP. An alternative method is proposed that has the following features: 1) Tie rankings are allowed; 2) all rank order information is incorporated into the estimation — not just first preferences; 3) the procedure is formulated as a L.P. model, which is easily implemented with existing software; 4) statistical inference is supported by the underlying stochastic model; and 5) it supports estimation of individual and group preferences.     

Estimating the effects of free trade agreements on international trade flows using matching econometrics

This paper provides the first cross-section estimates of long-run treatment effects of free trade agreements on members' bilateral international trade flows using (nonparametric) matching econometrics. Our nonparametric cross-section estimates of ex post long-run treatment effects are much more stable across years and have more economically plausible values than corresponding OLS cross-section estimates from typical gravity equations. We provide plausible estimates of the long-run effects of membership in the original European Economic Community (EEC) and the Central American Common Market (CACM) between 1960 and 2000 and the estimates confirm anecdotal reports of these agreements' effectiveness.     

Rational expectations and market efficiency in the U.S. live cattle futures market: The role of proprietary information

The role of proprietary information in forecasting and market efficiency in the U.S. live cattle futures market is investigated. Using a unique proprietary data source collected by a private firm, we test whether the initial estimates in the USDA Cattle on Feed Report and the Knight‐Ridder pre‐release forecasts are unbiased and efficient forecasts of final revised USDA Cattle on Feed Report numbers. We then use these results to test whether futures price movements are predictable based on information in the proprietary data. We also test whether the initial estimates from the Cattle on Feed Report have new information that moves prices once the information contained in the proprietary data source has been taken into account. Results suggest that the information contained in the proprietary data source does have statistically significant explanatory power for forecasting final revised Cattle on Feed Report numbers and for predicting short‐term price movements of futures contracts. The results are inconsistent with strong‐form market efficiency in the live cattle futures market. We also find that the initial estimates in the Cattle on Feed Report still have new information that moves prices even after accounting for the unique information in both the Knight‐Ridder pre‐release forecasts and the proprietary data. © 2004 Wiley Periodicals, Inc. Jrl Fut Mark 24:429–451, 2004     

A random coefficient autoregressive Markov regime switching model for dynamic futures hedging

The random coefficient autoregressive Markov regime switching model (RCARRS) for estimating optimal hedge ratios, which generalizes the random coefficient autoregressive (RCAR) and Markov regime switching (MRS) models, is introduced. RCARRS, RCAR, MRS, BEKK‐GARCH, CC‐GARCH, and OLS are compared with the use of aluminum and lead futures data. RCARRS outperforms all models out‐of‐sample for lead and is second only to BEKK‐GARCH for aluminum in terms of variancereduction point estimates. White's data‐snooping reality check null hypothesis of no superiority is rejected for BEKK‐GARCH and RCARRS for aluminum, but not for lead. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:103–129, 2006     

FDI,openness and income

This is an empirical study of the impact of foreign direct investment (FDI) on income. It presents cross-country evidence that inward FDI is positively correlated with income. In addition, an instrument for FDI is constructed to address the issue of endogeneity. The results show that instrumental-variables (IV) estimates of the impact of FDI on income are positive and greater than OLS estimates, similar to the findings on trade in Frankel and Romer (). The evidence in this paper suggests that inward FDI contributes to higher income, and favours the argument of Irwin and Terviö () that trade openness is subject to measurement error – in particular, trade is an imperfect proxy for many income-enhancing interactions between countries.     

Potential economic variables and actual economic policies in Europe

Ignoring for a moment the debate on whether balanced budget rules are a sensible idea from a macroeconomic point of view, there remains a major problem with tying one’s fiscal policy to econometric estimates of potential variables: their notorious unreliability. With every one of its biannual economic forecasts, the EC provides revised estimates of structural parameters that are crucial components of its macroeconometric models and, by extension, its economic policy advice. This article shows that the EC’s econometric estimates of potential growth variables in Europe have been subject to massive revisions since the financial crisis.     

The forward pricing function of the shipping freight futures market

This article investigates the unbiasedness hypothesis of futures prices in the freight futures market. Being the only market whose underlying asset is a service, it sets it apart from other markets investigated so far in the literature. Cointegration techniques, employed to examine this hypothesis, indicate that futures prices one and two months before maturity are unbiased forecasts of the realized spot prices, whereas a bias exists in the three-months futures prices. This mixed evidence is in agreement with studies in other markets and suggests that the acceptance or rejection of unbiasedness depends on the idiosyncrasies of the market under investigation and on the time to maturity of the contract. Despite the existence of a bias in the three-months prices, futures prices for all maturities are found to provide forecasts of the realized spot prices that are superior to forecasts generated from error correction, ARIMA, exponential smoothing, and random walk models. Hence it appears that users of the BIFFEX market receive accurate signals from the futures prices (regarding the future course of cash prices) and can use the information generated by these prices to guide their physical market decisions. © 1999 John Wiley & Sons, Inc. Jrl Fut Mark 19: 353–376, 1999     

Estimating national road crash fatalities using aggregate data

Injuries and fatalities from road traffic crashes have emerged a major public health challenge in Pakistan. Reliable estimates of road crash fatalities (RCF) of a country, is a vital element needed for identification and control of key risk factors, road-safety improvement efforts and prioritizing national health. Reliability of current annual RCF estimates for Pakistan becomes highly questionable due to serious underreporting. This study aimed to predict annual RCF for Pakistan using data from World Health Organization and International Road Federation sources. An ordinary least square (OLS) regression model that relates fatality rate with different explanatory variables was developed. RCF were predicted for Pakistan for year 2012 and 2013, and results were compared with national police reported estimates. Study results indicated that there is serious underreporting of RCF in Pakistan and immediate measures are needed to improve the existing road crash recording and reporting system at the national and subnational levels.     

The Asymmetric Commodity Inventory Effect on the Optimal Hedge Ratio

Hedging strategies for commodity prices largely rely on dynamic models to compute optimal hedge ratios. This study illustrates the importance of considering the commodity inventory effect (effect by which the commodity price volatility increases more after a positive shock than after a negative shock of the same magnitude) in modeling the variance–covariance dynamics. We show by in‐sample and out‐of‐sample forecasts that a commodity price index portfolio optimized by an asymmetric BEKK–GARCH model outperforms the symmetric BEKK, static (OLS), or naïve models. Robustness checks on a set of commodities and by an alternative mean‐variance optimization framework confirm the relevance of taking into account the inventory effect in commodity hedging strategies.     

Role of delivery options in basis convergence

The corn futures contract, traded on the Chicago Board of Trade, provides sellers with delivery options about the timing of delivery, the location of delivery, and the grade to be delivered. These options presumably have values that can vary from one delivery month to the next. The joint values of the timing and location options are estimated for each delivery month for the years 1989 through 1997. These estimates are then used in regression models to determine the degree to which they influence basis variability on the first day of the maturity month. Econometric models are also developed to see if the estimated implicit options values are useful in improving the forecasts of basis convergence over the 2‐month period prior to maturity. The results suggested that variation in the delivery options values in the corn futures contract does indeed help explain basis variability on the first day of maturity. An option‐value variable, based on estimated values two months prior to maturity, resulted in occasional, small improvements (from a statistical point of view) in the precision of forecasts. The existence of delivery options increases basis variability at maturity, but it is difficult to use this information to improve forecasts of basis convergence. One limitation of the analysis is that the Chicago cash market had few transactions per day during the sample period, and hence the reported spot prices may be inadequate for making high‐quality estimates of the options values. © 2002 Wiley Periodicals, Inc. Jrl Fut Mark 22:783–809, 2002