“Speculative Influence Network” during financial bubbles: application to Chinese stock markets

We introduce the Speculative Influence Network (SIN) to decipher the causal relationships between sectors (and/or firms) during financial bubbles. The SIN is constructed in two steps. First, we develop a Hidden Markov Model (HMM) of regime-switching between a normal market phase represented by a geometric Brownian motion and a bubble regime represented by the stochastic super-exponential Sornette and Andersen (Int J Mod Phys C 13(2):171–188, 2002) bubble model. The calibration of the HMM provides the probability at each time for a given security to be in the bubble regime. Conditional on two assets being qualified in the bubble regime, we then use the transfer entropy to quantify the influence of the returns of one asset i onto another asset j, from which we introduce the adjacency matrix of the SIN among securities. We apply our technology to the Chinese stock market during the period 2005–2008, during which a normal phase was followed by a spectacular bubble ending in a massive correction. We introduce the Net Speculative Influence Intensity variable as the difference between the transfer entropies from i to j and from j to i, which is used in a series of rank ordered regressions to predict the maximum loss (%MaxLoss) endured during the crash. The sectors that influenced other sectors the most are found to have the largest losses. There is some predictability obtained by using the transfer entropy involving industrial sectors to explain the %MaxLoss of financial institutions but not vice versa. We also show that the bubble state variable calibrated on the Chinese market data corresponds well to the regimes when the market exhibits a strong price acceleration followed by clear change of price regimes. Our results suggest that SIN may contribute significant skill to the development of general linkage-based systemic risks measures and early warning metrics.     

On the equilibrium properties of locational sorting models

Important to many models of location choice is the role of local interactions or spillovers, whereby the payoffs from choosing a location depend in part on the number or attributes of other individuals or firms that choose the same or nearby locations in equilibrium. This paper develops the equilibrium properties of a broadly applicable and readily estimable class of sorting models that allow location decisions to depend on both fixed local attributes (including unobserved attributes) and local interactions, describes the conditions under which equilibria exist and are unique, and provides a test for uniqueness in empirical analyses of sorting equilibrium.     

Optimal design of nonlinear experiments with parameter constraints

The nonlinear regression model with N observations y _i=η(x _i,θ) +ε_i, and with the parameter θ subject to q nonlinear constraints C _j (θ)=0; j=1, …,q, is considered. As an example, the spline regression with unknown nodes is taken. Expressions for the variances (variance matrices) of the LSE are discussed. Because of the complexity of these expressions, and the singularity of the variance matrix of the LSE for θ, the optimality criteria and their properties, in particular the convexity and the equivalence theorem are considered from different aspects. Also the possibility of restriction to designs with limited values of measures of nonlinearity is mentioned. Research supported by the VEGA-grant of the Slovak grant agency No. 1/7295/20.     

Estimation of possibly misspecified semiparametric conditional moment restriction models with different conditioning variables

Newey and Powell [2003. Instrumental variable estimation of nonparametric models. Econometrica 71, 1565–1578] and Ai and Chen [2003. Efficient estimation of conditional moment restrictions models containing unknown functions. Econometrica 71, 1795–1843] propose sieve minimum distance (SMD) estimation of both finite dimensional parameter (θ)$(\theta )$ and infinite dimensional parameter (h) that are identified through a conditional moment restriction model, in which h could depend on endogenous variables. This paper modifies their SMD procedure to allow for different conditioning variables to be used in different equations, and derives the asymptotic properties when the model may be misspecified  . Under low-level sufficient conditions, we show that: (i) the modified SMD estimators of both θ$\theta$ and h   converge to some pseudo-true values in probability; (ii) the SMD estimators of smooth functionals, including the θ$\theta$ estimator and the average derivative estimator, are asymptotically normally distributed; and (iii) the estimators for the asymptotic covariances of the SMD estimators of smooth functionals are consistent and easy to compute. These results allow for asymptotically valid tests of various hypotheses on the smooth functionals regardless of whether the semiparametric model is correctly specified or not.     

Probabilistic characterization of directional distances and their robust versions

In this work, we analyze the performance of production units using the directional distance function which allows to measure the distance to the frontier of the production set along any direction in the inputs/outputs space. We show that this distance can be expressed as a simple transformation of radial or hyperbolic distance. This formulation allows to define robust directional distances in the lines of α-quantile or order-m partial frontiers and also conditional directional distance functions, conditional to environmental factors. We propose simple methods of estimation and derive the asymptotic properties of our estimators.     

On bootstrapping the mode in the nonparametric regression model with random design

In the nonparametric regression model with random design and based on i.i.d. pairs of observations (X _i, Y _i), where the regression function m is given by m(x)=?(Y _i|X _i=x), estimation of the location θ (mode) of a unique maximum of m by the location of a maximum of the Nadaraya-Watson kernel estimator for the curve m is considered. In order to obtain asymptotic confidence intervals for θ, the suitably normalized distribution of is bootstrapped in two ways: we present a paired bootstrap (PB) where resampling is done from the empirical distribution of the pairs of observations and a smoothed paired bootstrap (SPB) where the bootstrap variables are generated from a smooth bivariate density based on the pairs of observations. While the PB requires only relatively small computational effort when carried out in practice, it is shown to work only in the case of vanishing asymptotic bias, i.e. of “undersmoothing” when compared to optimal smoothing for mode estimation. On the other hand, the SPB, although causing more intricate computations, is able to capture the correct amount of bias if the pilot estimator for m oversmoothes. Received: May 2000     

A flexible approach to parametric inference in nonlinear and time varying time series models

Many structural break and regime-switching models have been used with macroeconomic and financial data. In this paper, we develop an extremely flexible modeling approach which can accommodate virtually any of these specifications. We build on earlier work showing the relationship between flexible functional forms and random variation in parameters. Our contribution is based around the use of priors on the time variation that is developed from considering a hypothetical reordering of the data and distance between neighboring (reordered) observations. The range of priors produced in this way can accommodate a wide variety of nonlinear time series models, including those with regime-switching and structural breaks. By allowing the amount of random variation in parameters to depend on the distance between (reordered) observations, the parameters can evolve in a wide variety of ways, allowing for everything from models exhibiting abrupt change (e.g. threshold autoregressive models or standard structural break models) to those which allow for a gradual evolution of parameters (e.g. smooth transition autoregressive models or time varying parameter models). Bayesian econometric methods for inference are developed for estimating the distance function and types of hypothetical reordering. Conditional on a hypothetical reordering and distance function, a simple reordering of the actual data allows us to estimate our models with standard state space methods by a simple adjustment to the measurement equation. We use artificial data to show the advantages of our approach, before providing two empirical illustrations involving the modeling of real GDP growth.     

Location and the theory of production Clarifications and extensions

This paper has attempted to clarify some weaknesses and flaws contained in Miller and Jensen's analysis. In particular, we have demonstrated that in Miller and Jensen's model, if the production function is homogeneous of degree one and the transport rate functions are independent of quantities shipped, it is impossible to have an interior solution. In addition, we have evaluated the role of the generalized transport rate functions in the profit-maximization location model with and without a prescribed level of output and shown that if transport rates depend on quantities shipped and have constant elasticities, then a linearly homogeneous production function is not sufficient to insure that optimum location is independent of output or the demand function. This result clearly invalidates Miller and Jensen's assertion.     

A class of simple distribution-free rank-based unit root tests

We propose a class of distribution-free rank-based tests for the null hypothesis of a unit root. This class is indexed by the choice of a reference densityg, which need not coincide with the unknown actual innovation density f. The validity of these tests, in terms of exact finite-sample size, is guaranteed, irrespective of the actual underlying density, by distribution-freeness. Those tests are locally and asymptotically optimal under a particular asymptotic scheme, for which we provide a complete analysis of asymptotic relative efficiencies. Rather than stressing asymptotic optimality, however, we emphasize finite-sample performances, which also depend, quite heavily, on initial values. It appears that our rank-based tests significantly outperform the traditional Dickey-Fuller tests, as well as the more recent procedures proposed by Elliott et al. (1996), Ng and Perron (2001), and Elliott and Müller (2006), for a broad range of initial values and for heavy-tailed innovation densities. Thus, they provide a useful complement to existing techniques.     

Categorization and correlation in a random-matching game

We consider a random-matching model in which every agent has a categorization (partition) of his potential opponents. In equilibrium, the strategy of each player i is a best response to the distribution of strategies of his opponents (when they face i) in each category of his categorization. We provide equivalence theorems between distributions generated by equilibrium profiles and correlated equilibria of the underlying game.     

Testing conditional symmetry against one-sided alternatives in square contingency tables

For a (k×k) square contingency table with ordered categories, letX(Y) denote the row (column) number. The conditional symmetry model is given byP(X=i, Y=j|X<Y)=P(X=j, Y=i |X>Y), ∀i<j. In this paper, we study the likelihood ratio tests of conditional symmetry in a square contingency table against two particular classes of one-sided alternatives. We obtain the maximum likelihood estimators under each alternative. The asymptotic null distributions of the likelihood ratio statistics are shown to have chi-bar square type distributions. A simulation study is performed by comparing the powers of different tests. The theory developed is illustrated by using the famous eye vision data from Stuart (1953).     

A consistent nonparametric test for nonlinear causality—Specification in time series regression

Since the pioneering work by Granger (1969), many authors have proposed tests of causality between economic time series. Most of them are concerned only with “linear causality in mean”, or if a series linearly affects the (conditional) mean of the other series. It is no doubt of primary interest, but dependence between series may be nonlinear, and/or not only through the conditional mean. Indeed conditional heteroskedastic models are widely studied recently. The purpose of this paper is to propose a nonparametric test for possibly nonlinear causality. Taking into account that dependence in higher order moments are becoming an important issue especially in financial time series, we also consider a test for causality up to the Kth conditional moment. Statistically, we can also view this test as a nonparametric omitted variable test in time series regression. A desirable property of the test is that it has nontrivial power against T^1/2-local alternatives, where T is the sample size. Also, we can form a test statistic accordingly if we have some knowledge on the alternative hypothesis. Furthermore, we show that the test statistic includes most of the omitted variable test statistics as special cases asymptotically. The null asymptotic distribution is not normal, but we can easily calculate the critical regions by simulation. Monte Carlo experiments show that the proposed test has good size and power properties.     

Redistributing the energy tax burden in the Philippines

This paper uses an aggregate modelling approach to assess the impacts of a redistribution of the taxes and duties that currently exist on crude oil and refined petroleum products on the Philippine economy. The approach used in the analysis consists of a general equilibrium model composed of fourteen producing sectors, fifteen consuming sectors, three household categories classified by income and a government. The effects of replacing the taxes and duties on crude oil and refined petroleum products with a more broad based tax on manufacturing and service sectors output on prices and quantities are examined. The results are revealing. For example, the consequences of redistributing the tax burden away from petroleum products to the manufacturing and service sectors of the Philippine economy will be an increase in output by all producing sectors of about 3.5 percent or about 2.4 hundred billion Philippine pesos, a rise in the consumption of goods and services by about 6.1 percent or 1.6 hundred billion Philippine pesos, a rise in total utility by 6.9 or 1.9 hundred billion Philippine pesos, and virtually no change in tax revenue for the government. When subjected to a sensitivity analysis, the results are reasonably robust with regard to the assumption of the values of the substitution elasticities. That is, while the model's equilibrium values do vary in response to different assumptions of the values of these elasticities, the fluctuations are not so enormous to suggest that the model is unrealistically sensitive to these parameters.Notation Y _j Total production in sectorj (j=1, 2, ..., 14) - CD _j Consumer demand for productj - GE _j Government endowment of productj - UM _j Imports of productj - _LRAS_jl RAS balanced input-output intermediate demands - GD _j Government demand for productj - INV _j Investment in sectorj - UX _j Exports of productj - SL _c Supply of labor by householdc (c=1, 2, 3) - SK _c Supply of capital by householdc - SD _c Supply of land by householdc - DL _j Demand for labor in the industryj - DK _j Demand for capital in the industryj - DD _j Demand for land in industryj - GDL Government demand for labor - GDD Government demand for land - TL _j Tax on labor in industryj - TK _j Tax on capital in industryj - TD _j Tax on land in industryj - GCE _i Consumer demand for consumer producti (i=1, 2, ..., 15) - Z _ji A 14×15 transformation matrix - RCS _ic RAS balanced matrix of each household's demand for each consumer good - TC _j Excise tax on consumer goodj - TRN _c Transfer payment to householdc - PIT _c Personal income tax payment for householdc - TAU _c Marginal income tax rate for householdc - SAV _c Savings in householdc - GC _c Gross consumption of householdc - ZTA Consumption plus leisure coefficient - TE Total government endowments - EM _j Demand elasticity of export demand - FE _j Endowment/demand sector of adjusted elasticity of export demand - GSK _j Government endowment of capital in industryj - GDK _j Government demand for capital in industryj - GTL Government wage taxes on its own employees - TXO _j Government output tax on industryj - TC _c Consumption taxes on householdc - CG _c Total government consumption by householdc - SAV _c Total savings by householdc - INV _j Total investment by industryj The views expressed are those of the authors and do not necessarily represent the policies of the organizations with which they are affiliated. They would like to thank Wildrido Cruz of the World Bank and Climenta Habido of the Philippine government for help in acquiring the requisite data to calibrate the model used in the analysis. They would also like to thank an anonymous referee for helpful suggestions.     

Forecasting by factors,by variables,by both or neither?

We consider forecasting with factors, variables and both, modeling in-sample using Autometrics so all principal components and variables can be included jointly, while tackling multiple breaks by impulse-indicator saturation. A forecast-error taxonomy for factor models highlights the impacts of location shifts on forecast-error biases. Forecasting US GDP over 1-, 4- and 8-step horizons using the dataset from Stock and Watson (2009) updated to 2011:2 shows factor models are more useful for nowcasting or short-term forecasting, but their relative performance declines as the forecast horizon increases. Forecasts for GDP levels highlight the need for robust strategies, such as intercept corrections or differencing, when location shifts occur as in the recent financial crisis.     

Endogenous R&D spillovers and locational choice with discriminatory pricing

We present a model of spatial price discrimination where R&D spillovers are endogenous as they depend on firms' location. We establish that both the distance between locations and R&D efforts are an increasing function of the transportation cost coefficient and show that there is a continuum of cases where firms will choose an intermediate location. The managerial implications from the model are discussed using examples of marketing behavior by Internet retailers. Copyright © 2004 John Wiley & Sons, Ltd.     

Derivation of a joint occupancy distribution via a bivariate inclusion and exclusion formula

Consider a supply of balls randomly distributed into n distinguishable urns and assume that the number of balls distributed into any specific urn is a random variable with probability function . The joint probability function and binomial moments of the number K_i of urns occupied by i balls each and the number K_j of urns occupied by j balls each, i≠j, given that a total of S_n=m balls are distributed into the n urns, are derived in terms of convolutions of q_x, x=0,1, . . . and their finite differences. Also, some illustrating examples are discussed.     

Exact and superlative index numbers

The paper rationalizes certain functional forms for index numbers with functional forms for the underlying aggregator function. An aggregator functional form is said to be ‘flexible’ if it can provide a second order approximation to an arbitrary twice diffentiable linearly homogeneous function. An index number functional form is said to be ‘superlative’ if it is exact (i.e., consistent with) for a ‘flexible’ aggregator functional form. The paper shows that a certain family of index number formulae is exact for the ‘flexible’ quadratic mean of order r aggregator function, $\text{(Σ}{}_{\mathrm{i}}\text{Σ}{}_{\mathrm{j}}\text{a}{}_{\mathrm{ij}}\text{x}{}_{\mathrm{i}}\text{r}\text{2}\text{x}{}_{\mathrm{j}}\text{r}\text{2}\text{)}{}^{\mathrm{<mtext>1</mtext><mtext>r</mtext>}}\text{,}$ defined by Den and others. For r equals 2, the resulting quantity index is Irving Fisher's ideal index. The paper also utilizes the Malmquist quantity index in order to rationalize the Törnqvist-Theil quantity indexin the nonhomothetic case. Finally, the paper attempts to justify the Jorgenson-Griliches productivity measurement technique for the case of discrete (as opposed to continuous) data.     

Adaptive estimation of the dynamics of a discrete time stochastic volatility model

This paper is concerned with the discrete time stochastic volatility model _Yi=exp(_Xi/2)_ηi$Y_i=exp(X_i/2){\eta }_i$, _Xi+1=b(_Xi)+σ(_Xi)_ξi+1$X_{i+1}=b\left(X_i\right)+\sigma \left(X_i\right){\xi }_{i+1}$, where only (_Yi)$\left(Y_i\right)$ is observed. The model is rewritten as a particular hidden model: _Zi=_Xi+_εi$Z_i=X_i+{\epsilon }_i$, _Xi+1=b(_Xi)+σ(_Xi)_ξi+1$X_{i+1}=b\left(X_i\right)+\sigma \left(X_i\right){\xi }_{i+1}$, where (_ξi)$\left({\xi }_i\right)$ and (_εi)$\left({\epsilon }_i\right)$ are independent sequences of i.i.d. noise. Moreover, the sequences (_Xi)$\left(X_i\right)$ and (_εi)$\left({\epsilon }_i\right)$ are independent and the distribution of ε$\epsilon$ is known. Then, our aim is to estimate the functions b$b$ and σ²${\sigma }^2$ when only observations _Z1,…,_Zn$Z_1,\dots ,Z_n$ are available. We propose to estimate bf$bf$ and (b²+σ²)f$(b^2+{\sigma }^2)f$ and study the integrated mean square error of projection estimators of these functions on automatically selected projection spaces. By ratio strategy, estimators of b$b$ and σ²${\sigma }^2$ are then deduced. The mean square risk of the resulting estimators are studied and their rates are discussed. Lastly, simulation experiments are provided: constants in the penalty functions defining the estimators are calibrated and the quality of the estimators is checked on several examples.     

Proportional distribution schemes

An amount of income can be obtained jointly by m agents, the ith agent's share of income being θ_i. The income and the utilities of each agent are functions of the state of nature. Each agent has a probability measure over the states of nature. An efficient proportional distribution is one which is (1) Pareto optimal and for which (2) the expected proportion of income agent i recieves divided by θ_i is independent of i. It is shown that if the attitudes are strictly concave then there exists exactly one proportional distribution scheme. Furthermore, in special cases, each agent expects to recieve an income that exceeds his share.     

A characterization of the exponential distribution by higher order gap

Summary SupposeX is a non-negative random variable with an absolutely continuous (with respect to Lebesgue measure) distribution functionF (x) and the corresponding probability density functionf(x). LetX ₁,X ₂,...,X _n be a random sample of sizen fromF andX _i,n is thei-th smallest order statistics. We define thej-th order gapg _i,j(n) asg _i,j(n)=X _i+j,n–X_i,n 1i<n, 1nn–i. In this paper a characterization of the exponential distribution is given by considering a distribution property ofg _i,j(n).