On nonparametric latent trait models

Some nonparametric latent trait models for dichotomous data are considered. We deal with n subjects, each answering to the same set of of k items, each item being scored dichotomously. We are interested in ordering item difficulties α₁,...α_k . In Sec. 2 it is shown that in the considered nonparametric models the ordering is identifiable. Then an order estimator is defined and its quality is described by the probabilities of correct, wrong and deferred decision. Asymptotic behaviour of these probabilities are considered for n→∞ and any k≥2. The hypothesis that the probability of wrong decision diminishes when the model is “more distant” from so called random response model, is proved for n≤3 and verified numerically for n≥3. In Sec. 4 we discuss critically some parameters of nonparametric models known in the literature as “coefficients of scalability”. In particular, for k=2 their connections with the evaluation of positive dependence are considered.     

Cointegration and distance between differenced processes

In this note, it is argued that cointegration augments the distance between the differenced series. If two series, x _t and y _t , are integrated of order one and cointegrated and v _t and w _t are integrated of order one but not cointegrated then, under certain conditions, the distance between ??x _t and ??y _t is more than the distance between ??v _t and ??w _t .     

An assessment of China's joint prevention and control policy on sulfur dioxide emissions reduction: A spatial econometric analysis

Sulfur dioxide (SO₂) is a typical pollutant that affects human health, climate, and environmental and ecological conditions. China has been experiencing high concentrations of SO₂, particularly in urban areas, since the 1990s. In 2010, a “joint prevention and control” (JPC) policy was issued to address air pollution problems and strengthen the regulation of SO₂ emissions. This study aimed to describe the mitigation effects of this policy on SO₂ emissions in 116 Chinese cities from 2003 to 2017. We applied global and local Moran's I indices to confirm the presence of significant spatial autocorrelation in SO₂ emissions and constructed four spatial models to assess the effect of the JPC policy in reducing SO₂ emissions and its transmission mechanism. We found that the policy decreased SO₂ emissions by 1.89 × 10⁴ tons, SO₂ intensity by 1.70 tons per km², and SO₂ per capita of 158.49 tons per 10,000 people in each city, on average, all of which are significant changes. The empirical results also show that population growth, economic structure, and environmental protection significantly decrease SO₂ emissions. Finally, we recommended policies to encourage regional cooperation under the JPC policy, with the aim of promoting further reductions in SO₂ emissions.     

Assessing the Economic Benefits to Agriculture from Air Pollution Control

Agricultural crop production is highly dependent upon environmental conditions among which air quality plays a central role. Various air pollutants have been identified as a potential influence on commercial crops including SO₂, NOx, O₃ and CO₂. In particular, ozone in the lower atmosphere has been identified as a serious cause of crop loss in the United States and seems likely to be creating similar losses in Europe. In this paper the methods which can be applied to assess the economic damages from air pollution are critically reviewed. This requires measuring pollutant concentrations, relating these to physical crop damages, and estimating the reactions of the agricultural sector and consumers to give welfare changes in terms of consumers’ surplus and producers’ quasi-rents. The approach of the European open-top chamber programme (EOTCP) is shown to have neglected lessons learnt by the National Crop Loss Assessment Network (NCLAN) in the US     

The impact of public regulation on housing quality and on structural changes

This paper represents a theoretical investigation of profit maximizing behavior of a landlord under rent control. The situation envisioned is one that the landlord owns, free and clear, either two housing units ready to merge or one large one ready to convert into two small ones; in each case the units are already in place, such that capital costs are sunk and treated as bygones. Each unit has a technology of production of housing services with a fixed input of quantity of space (shelter) and a variable input of quality, that is affected by physical ageing (non-controllable) and by maintenance (controllable). At starting time t₀, we have a state of quality and a historical state of initial quality Q?_i, at the time the building was built, with the implicit constraint that Q_i(t) < Q?_i, for all t> t₀. The analysis addresses the general question of housing structural changes—conversion or merger—and how these changes are being accelerated under the threat of rent control.     

Revelations of a gambler

Knowing that a decision maker maximizes expected utility with respect to some (unknown) utility U and some (unknown) probability P, what can one tell about P by observing his decisions? We discuss this revealed preference question primarily in the simple case of a two-element (H and T) state space, and show that the possible revelations of P_T/P_H are precisely those of the form P_T/P_Hε∪^K_k=1 (γ_k,δ_k), for some algebraic numbers γ_k,δ_k.     

A PLS path model to investigate the relations between institutions and human development

The paper studies the relations between institutions and human development, in particular the causal effects of the different types of institutions on different components of human development. We assume development to be created by aggregate demand; in particular that aggregate demand determines the material components of human development. We thus divide institutions into those that create demand and those that are determined by the whole process of development. Similarly we divide human development in its three traditional components (economic development, health, knowledge). Both human development and institutions are assumed to be multidimensional constructs; all the main components of these constructs are defined as latent variables, and the relations between them as structural relations. A partial least squares (PLS) path model is developed: it is the aggregation (and simultaneous estimation) of an outer model relating observed or manifest variables to their own latent variable and of a structural model (inner model) relating some endogenous latent variable to other latent variables. From the goodness of fit point of view, our results seem to validate our theoretical assumptions.     

Characterization of the exponential distribution function by Properties of the differenceX k+s∶n−X k∶n of order statistics

We considern independent and identically distributed random variables with common continuous distribution functionF concentrated on (0, ∞). LetX _1∶n≤X_2∶n...≤X_n∶n be the corresponding order statistics. Put $$d_s \left( x \right) = P\left( {X_{k + s:n} - X_{k:n} \geqslant x} \right) - P\left( {X_{s:n - k} \geqslant x} \right), x \geqslant 0,$$ and $$\delta _s \left( {x, \rho } \right) = P\left( {X_{k + s:n} - X_{k:n} \geqslant x} \right) - e^{ - \rho \left( {n - k} \right)x} ,\rho > 0,x \geqslant 0.$$ Fors=1 it is well known that each of the conditions d₁(x)=O ?x≥0 and δ₁ (x, p) = O ?x≥0 implies thatF is exponential; but the analytic tools in the proofs of these two statements are radically different. In contrast to this in the present paper we present a rather elementary method which permits us to derive the above conclusions for somes, 1≤n —k, using only asymptotic assumptions (either forx→0 orx→∞) ond _s(x) and δ₁ (x, p), respectively.     

Methodological problems in gender and media research

This paper will focus on the main questions that have arisen from a methodological point of view relating to the theoretical and research area of gender and media, which continues to be the subject of discussion and debate. The methodology chosen by scholars has changed over the course of time, depending on: the interpretative paradigm underlying the researchers (especially from the feminist perspective which leads the analysis, due to the theme); the sociocultural context; the type of contents offered by the media (old, new media); and technological innovations in the communications field. In particular, the author underlines that scholars who adopt the equality between the sexes perspective tend to favour quantitative methods, while scholars oriented towards highlighting sexual and gender differences tend to favour qualitative methods.     

Improved stein-rule estimator for regression problems

Stein-Rule estimator for regression problems has been studied by several authors including Sclove (1968) and others listed in Vinod's (1978) survey. Ullah and Ullah (1978) provide the expressions for the mean squared error (MSE) of a double k-class (KK) estimator with parameters k₁ and k₂. When k₂=1 the Stein-Rule estimator becomes a special case of KK and an optimal choice of k₁ is known. This paper explores optimal theoretical choice of k₁ and k₂. We note that negative choices of k₂ are permissible, and that thereis a large range of choices for K₁ and k₂ where the MSE of the Stein-Rule estimator can be reduced for regression problems based on multicollinear data. A simulation experiment is included.     

Berry-Esséen rate in asymptotic normality for perturbed sample quantiles

In estimating quantiles with a sample of sizeN obtained from a distributionF, the perturbed sample quantiles based on a kernel functionk have been investigated by many authors. It is well known that their behaviour depends on the choices of “window-width”, sayw _N. Under suitable and reasonably mild assumptions onF andk, Ralescu and Sun (1993) have recently proven that lim _N→∞ N ^1/4w_N=0 is the necessary and sufficient condition for the asymptotic normality of the perturbed sample quantiles. In this paper, their rate of convergence is investigated. It turns out that the optimal Berry-Esséen rate ofO(N^?1/2) can be achieved by choosing the window-width suitably, sayw _N=O(N^?1/2). The obtained results, in addition to being explicit enough to verify the sufficient condition for the asymptotic normality, improve Ralescu's (1992) result of which the rate is of order (logN)N ^?1/2.     

Randomized experiments from non-random selection in U.S. House elections

This paper establishes the relatively weak conditions under which causal inferences from a regression–discontinuity (RD) analysis can be as credible as those from a randomized experiment, and hence under which the validity of the RD design can be tested by examining whether or not there is a discontinuity in any pre-determined (or “baseline”) variables at the RD threshold. Specifically, consider a standard treatment evaluation problem in which treatment is assigned to an individual if and only if V>_v0$V>v_0$, but where _v0$v_0$ is a known threshold, and V is observable. V can depend on the individual's characteristics and choices, but there is also a random chance element: for each individual, there exists a well-defined probability distribution for V  . The density function—allowed to differ arbitrarily across the population—is assumed to be continuous. It is formally established that treatment status here is as good as randomized in a local neighborhood of V=_v0$V=v_0$. These ideas are illustrated in an analysis of U.S. House elections, where the inherent uncertainty in the final vote count is plausible, which would imply that the party that wins is essentially randomized among elections decided by a narrow margin. The evidence is consistent with this prediction, which is then used to generate “near-experimental” causal estimates of the electoral advantage to incumbency.     

A note on compact differentiability and theδ-method

Letη _n ,n ∈ ?, be arbitrary functions defined on a probability space (ω,A,P) with values in a normed vector spaceB ₁ ,μ ∈ B ₁ andξ ₀ a separable random element inB ₁ such thatξ _n :=√n(η _n ?μ) converges weakly toξ ₀ in the sense of Hoffmann-Jørgensen. Then with (B ₂, ∥·∥₂) being another normed vector space andφ:B ₁→B ₂ compactly differentiable atμ with derivateD _μ, the random variable $\parallel \sqrt n (\phi (n_n ) - \phi (\mu )) - D_\mu (\sqrt n (n_n - \mu ))\parallel 2*$ converges to 0P-stochastically where “*” denotes the measurable cover. We show that the classicalδ — method extends to the non-measurable case where in the proof we shall not make use of any representation theorems but only of a slight refinement of the usual characterisation of compact differentiability, due to the fact that we will not assume {ξ _n :n ∈ ?} being tight.     

Steiner minimal trees and urban service networks

The optimal configuration of urban service networks has recently been shown to be a computationally difficult problem. However, there are efficient and effective techniques by which this optimal configuration of urban service networks can be approximated. In this paper, we analyze the L_p Steiner Network problem in the plane R² and demonstrate its applicability to the urban service network problem. We present a simple algorithm for estimating the L_p metric parameter for random points in the plane, then utilize it to find the L_p values for four different American cities. Finally, we apply the L_pSMT algorithm described within the text to one of the cities in order to demonstrate the effectiveness of our algorithm for determining optimal network configurations.     

Almost sure central limit theorem for the products of <Emphasis Type="Italic">U</Emphasis>-statistics

Let (X _n ) be a sequence of i.i.d random variables and U _n a U-statistic corresponding to a symmetric kernel function h, where h ₁(x ₁) = Eh(x ₁, X ₂, X ₃, . . . , X _m ), μ = E(h(X ₁, X ₂, . . . , X _m )) and ? ₁ = Var(h ₁(X ₁)). Denote \({\gamma=\sqrt{\varsigma_{1}}/\mu}\), the coefficient of variation. Assume that P(h(X ₁, X ₂, . . . , X _m ) > 0) = 1, ? ₁ > 0 and E|h(X ₁, X ₂, . . . , X _m )|³ < ∞. We give herein the conditions under which

$\lim_{N\rightarrow\infty}\frac{1}{\log N}\sum_{n=1}^{N}\frac{1}{n}g\left(\left(\prod_{k=m}^{n}\frac{U_{k}}{\mu}\right)^{\frac{1}{m\gamma\sqrt{n}}}\right) =\int\limits_{-\infty}^{\infty}g(x)dF(x)\quad {\rm a.s.}$

for a certain family of unbounded measurable functions g, where F(·) is the distribution function of the random variable \({\exp(\sqrt{2} \xi)}\) and ξ is a standard normal random variable.

     

Third-order optimum properties of estimator-sequences

SequencesT ⁽ⁿ⁾ ,n∈N, are considered, whereT ⁽ⁿ⁾ estimates a vector parameter ?∈R ^p from an i.i.d. sample of sizen, and such sequences are compared on the basis of their risks ∫L(n ^1/2(T ⁿ (x)?θ))P _θ ⁿ (dx) relative to loss functionsL:R ^p →R. A characterization is given for sequencesT ^*(n) ,n∈N, which generate an essentially complete class in the following sense: For any sequenceT ⁽ⁿ⁾ ,n∈N, there exist functions Φ _n ,n∈N, such that forn→∞ we have $$\begin{gathered} \smallint L (n^{1/2} (T^{*(n)} + n^{ - 1} \Phi _n (T^{*(n)} ) - \theta )) dP_\theta ^n \leqslant \hfill \\ \leqslant \smallint L (n^{1/2} (T^{(n)} - \theta )) dP_\theta ^n + o (n^{ - 1} ), \hfill \\ \end{gathered} $$ for every ? and everyL satisfying certain conditions. If the estimator-sequences are compared by their risks ∫W(T ⁽ⁿ⁾ d P _θ ⁿ ,θ) with respect to loss functionsW:R ^p ×Θ→R then a similar result on asymptotically complete classes is valid. The results are obtained under the assumption thatT ^*(n) ,n∈N, andT ⁽ⁿ⁾ ,n∈N, admit stochastic expansions which are sufficiently regular, that the loss functionsL andW are sufficiently smooth and bounded by polynomials, and that the estimator-sequences have asymptotically bounded moments; the latter condition is not needed for bounded functionsL andW.     

Estimation in a disequilibrium model and the value of information

Suits' model of the watermelon market is reformulated as a disequilibrium model and the likelihood function is derived under various assumptions concerning the amount of available information. Such models are characterized by a min condition as in y_t = min(D_t, S_t) for an ordinary demand-supply model, where the observed quantity y_t is the smaller demand and supply. Varying amounts of information may be available depending on which variables are observed and on whether prior information is available for separating the sample into subsets for which D_t < S_t and conversely. The likelihood function corresponding to the least amount of prior information is shown to be unbounded without a certain variance ratio restriction. Computations are successfully carried out both with the original model and Monte Carlo experiments and the effect of different amounts of information on MSE's is analyzed.     

Estimation in the first-order moving average model through the finite autoregressive approximation: Some asymptotic results

To estimate α in the model y_t = u_t+αu_t?1, we consider a proposal by Durbin (Biometrika, 1969). It consists in fitting an autoregression of order k to the data, and deriving from there an estimate α^. The probability limit and the variance of the limiting normal distribution of α^ are presented and discussed in detail, when the sample size T → ∞, but k remains fixed. The differences between the resulting values and those corresponding to the maximum likelihood estimator are exponentially decreasing functions of k. Several modifications of the estimator are discussed and found consistent, but asymptotically inefficient.     

An evaluation framework for developing green infrastructure by using a new hybrid multiple attribute decision-making model for promoting environmental sustainability

With the expansion of urbanization caused by the growth of population and industrial activities, the urban/city and suburban areas are facing a variety of environmental threats. Although more research and urban policy has advocated and practiced the development of green infrastructure (GI) to support urban sustainable environment, the evaluation framework for the development of GI for promoting environmental sustainability is still insufficient. Moreover, the Analytic Hierarchy Process (AHP) commonly applied in published literature, makes an unrealistic assumption of independent relationships among dimensions/criteria in decision making for satisfying the real-world problem. Therefore, the purpose of this study is to construct the evaluation framework, including four dimensions and related ten criteria, using a new hybrid-modified multiple attribute decision-making (MADM) model for developing and improving the GI for promoting environmental sustainability. This MADM model is combined with three different methodologies of MADM, including the Decision-Making Trial and Evaluation Laboratory (DEMATEL) for constructing the influential network relation map (INRM) to explore the complex influential inter-relationships and DEMATEL based on Analytic Network Process (DANP) for determining the influential weights with the VIse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) for evaluating and presenting improvement strategies for six different GIs. The empirical study indicates that DEMATEL and DANP Results suggest that decision-makers should pay more attention to the improvement of Design (D₄) and Materials (D₂) in terms of dimensions when utilizing the GI to promote environmental sustainability. Because these dimensions are enhanced, Species (D₁) and Energy (D₃) will be improved in synchronization. From the perspective of criteria, five are key core criteria and need to be focused on first: increasing the green coverage rate (B₉), utilizing sustainable materials (B₄), using ecological engineering (B₈), shaping species biodiversity (B₁), and reducing energy consumption (B₅). Modified VIKOR reveals that “grass swales” are a comparatively better choice among six GIs for promoting environmental sustainability toward achieving the aspiration level. Therefore, this MADM model is beneficial to provide a more convincing assessment framework and improvement strategies for the development of GI for promoting environmental sustainability. As a result, these modified MADM models can be shown more conveniently and reasonably than traditional methods such as traditional AHP or ANP method.     

Mediated power and outsourcing relationships

Mediated power is often used by firms to control the behaviors or influence the decisions of other members of the value chain. Interestingly, significant contributions in the academic literature offer consistent evidence that the use of mediated power has a negative impact on the quality of inter-organizational relationships. Yet, there is a dearth of empirical research investigating the conditions under which the use of mediated power is more or less prevalent. Utilizing dyadic data collected on 102 outsourcing relationships, this study evaluates how the buying firm's dependence on the service provider, asserted importance of the outsourced activity, and difficulties with other inter-organizational control mechanisms are related to their reliance on mediated power. Results from our hierarchical regression analysis support the hypotheses that the use of mediated power is diminished when the buyer is currently more dependent on the service provider due to switching difficulties and the buyer has a higher expectation of future supply market consolidation. Similar hypotheses regarding the effect of the strategic importance of the outsourced activity and entry barriers to the service provider's market were not supported. The results also support the hypothesis that the use of mediated power is more pronounced when the buyer experiences contract management difficulties, but the same is not true when the buyer has difficulty in monitoring the provider. To our knowledge, these findings represent the first empirical explanation of conditions which either attenuate or exacerbate the use of mediated power by outsourcing organizations.