Does Trade Openness Affect the Speed of Output Convergence? Some Empirical Evidence

In this paper we develop flexible techniques for measuring the speed of output convergence between countries when such convergence may be of an unknown non-linear form. We then calculate these convergence speeds for various countries, in terms of half-lives, using a time-series data-set for 88 countries. These calculations are based on both nonparametric kernel regression and ‘fuzzy’ regression, and the results are compared with more restrictive estimates based on the assumption of linear convergence. The calculated half-lives are regressed, again in various flexible ways, on cross-section data for the degree of openness to trade. We find evidence that favors the hypothesis that increased trade openness is associated with a faster rate of convergence in output between countries.     

How well do children insure parents against low retirement income? An analysis using survey data from urban China

As population aging becomes more pronounced in the developing world, the uneven implementation of social safety nets raises important questions as to how well traditional family-based mechanisms insure elderly incomes when pension systems fail. Using a unique dataset from a recent household survey conducted in urban China, we find evidence that private transfers respond to low household income of retired workers when income falls below the poverty line. This finding is consistent with an altruistic motive for transfers at low levels of household income. At the same time, however, the transfer response to elderly pre-transfer income is not sufficient to fully cover shortfalls that arise with severe pension arrears and low retirement income.     

Improving Financial Reports by Revealing the Accuracy of Prior Estimates*

Several researchers (e.g., Lundholm 1999; Ryan 1997; Petroni, Ryan, and Wahlen 2000) have proposed a reporting mechanism to enhance the reliability of estimates and other forward‐looking information in financial reports. Their proposals require companies to report reconciliations of prior‐year estimates to actual realizations as supplemental information in their financial reports. Such disclosures would enable investors to distinguish between accurate and opportunistic reporting behavior, and, arguably, should create incentives for companies to estimate accurately in the first place. Our study provides evidence on these proposals. Specifically, we conduct two experiments within the context of an important intangible asset requiring estimation ‐ software development costs. Our results show that the proposed reporting mechanism is effective in communicating information about the accuracy of financial estimates. We find, however, that not all disclosures are equally useful. The most effective disclosures explicitly describe the implications of misestimation (if any) on both the balance sheet and on earnings, thereby reducing the computational complexity associated with less explicit disclosures. Furthermore, our results show that when the disclosures explicitly describe the implications of misestimation, investors reward accurate estimators but do not explicitly punish those who are inaccurate. We conclude that information about previous estimate accuracy is useful to investors and that regulators should consider the type of disclosure, because not all disclosures may be equally effective in creating management incentives for accurate estimation. Moreover, the competitive advantage conferred on firms that provide accurate estimates arguably should create incentives for all companies to estimate accurately in the future.     

Analysing multi-level Monte Carlo for options with non-globally Lipschitz payoff

Giles (Oper. Res. 56:607–617, 2008) introduced a multi-level Monte Carlo method for approximating the expected value of a function of a stochastic differential equation solution. A key application is to compute the expected payoff of a financial option. This new method improves on the computational complexity of standard Monte Carlo. Giles analysed globally Lipschitz payoffs, but also found good performance in practice for non-globally Lipschitz cases. In this work, we show that the multi-level Monte Carlo method can be rigorously justified for non-globally Lipschitz payoffs. In particular, we consider digital, lookback and barrier options. This requires non-standard strong convergence analysis of the Euler–Maruyama method.      

Correcting for selectivity bias in the estimation of road crash costs

Police road crash data comprise a non-random sample of the true population of road crashes, the bias being due to the existence of crashes that are not notified to the Police. Heckman viewed similar problems as ‘omitted variables’ problems in that the exclusion of some observations in a systematic manner (so-called selectivity bias) has inadvertently introduced the need for an additional regressor in least squares procedures. In the case of Police road crash data, selectivity bias arises from factors affecting the notification of crashes to the Police, such as the number of vehicles in the crash and the type and location of the crash. Using Heckman's methodology for correcting for this selectivity bias, Police road crash data for Western Australia are reconciled with total road crash data in the estimation of the property damage costs of road crashes.     

EXPECTED VALUES OF COSTS AND REVENUES DEPENDENT ON DROUGHT†

In earlier papers on drought, sequences of wet and dry months were treated as realisations of binomial trials with periodic probabilities of failure (dry months), and the cost-revenue outcomes of alternative drought strategies were handled probabilistically. When costs and revenues may be represented by a set of second degree polynomials over a set of adjacent subranges of the time scale, their expectation may be expressed as a simple closed formula in the twelve probabilities of dry months. As an illustration of the use of these new formulae, means and standard deviations of drought duration calculated in this manner are presented for three typical localities in Queensland. Previously known closed formulae for the mean and the variance in the case where all calendar months have equal probability of being dry emerge as special cases and are verified.     

Estimating the long-term effects of utility energy conservation programs: A Pacific Northwest example

The Bonneville Power Administration operated a Residential Weatherization Pilot Program from 1980 through 1982. The program provided free home energy audits to 7200 electrically heated homes in the Pacific Northwest and gave zero-interest loans to weatherize 4100 of these homes. The total cost of the program was almost $11 million.The pilot program and its regionwide successor are intended to provide benefits to the Pacific Northwest region for roughly 30 years in terms of reduced residential energy consumption. Therefore, it is important to determine the durability of the electricity savings due to the program. Estimates of long-term savings affect power supply planning in the region and influence the economics of the program itself (i.e., the level of funding that BPA can justify for the program).This article presents empirical results concerning the total and net energy-saving affects of the BPA pilot program 1, 2, and 3 years after participation. The total annual electricity saving experienced by households that received an energy audit and a weatherization loan averaged 5300 kWh 1 year after participation, increasing to 6000 and 6500 kWh 2 and 3 years after participation, respectively. The net annual electricity saving that can be directly attributed to the program for these audit plus loan households averaged 4500 kWh (15% of preprogram use) 1 year after participation and declined slightly to about 4300 kWh 2 years and 4200 kWh 3 years after participation.The article uses these empirical findings with a simple simulation model to estimate the effects of the program into the future. Assuming that electricity prices remain constant after 1984, total energy savings increase to a level of 7000 kWh, while net energy savings decrease to 3600 kWh for the audit plus loan households. Alternative electricity price scenarios are discussed.     

ELECTION MANIFESTO POLICIES COMPARED

In this Forecast Release we compare the likely outcomes of the economic policies proposed by the three main contenders in the General Election. The results of some Dolicies. such as Labour's import controh and exchannge controls and the Allianie incomes policy, aie particularly dificult to evaluate using a conventional model; even for Conservative policies which are similar to those pursued so far, there remains considerable uncertainty about their consequences in future years. We have therefore prepared two forecasts for each of the three parties. One of these forecasts assumes that their policies are broadly successful, the other assumes they are unsuccessful.     

On the Inconsistency of Instrumental Variables Estimators for the Coefficients of Certain Dummy Variables

In this paper we consider the asymptotic properties of the Instrumental Variables (IV) estimator of the parameters in a linear regression model with some random regressors, and other regressors that are dummy variables. The latter have the special property that the number of non-zero values is fixed, and does not increase with the sample size. We prove that the IV estimator of the coefficient vector for the dummy variables is inconsistent, while that for the other regressors is weakly consistent under standard assumptions. However, the usual estimator for the asymptotic covariance matrix of the I.V. estimator for all of the coefficients retains its usual consistency. The t-test statistics for the dummy variable coefficients are still asymptotically standard normal, despite the inconsistency of the associated IV coefficient estimator. These results extend the earlier results of Hendry and Santos (Oxf Bull Econ Stat 67:571–595, 2005), which relate to a fixed-regressor model, in which the dummy variables are non-zero for just a single observation, and OLS estimation is used.