CONSERVATIVE ESTIMATING FUNCTION IN THE NONLINEAR REGRESSION MODEL WITH AGGREGATED DATA

The purpose of this paper is to study the theory of conservative estimating functions in nonlinear regression model with aggregated data. In this model, a quasi-score function with aggregated data is defined. When this function happens to be conservative, it is projection of the true score function onto a class of estimation functions. By constructing, the potential function for the projected score with aggregated data is obtained, which have some properties of log-likelihood function.

The Impact of Agricultural Import Tariff on Economic Growth： Evidence From Mercosur Countries

This research paper attempts to determine the relationship between agricultural import tariff and economic growth of Mercosur countries over the period 1996-2007 using regression analysis as well as evaluates the gains and losses from the group＇s trade policy over the same period. The introductory part of this paper focuses on the dynamics of changes in economic growth, trade, and import tariff of these countries over the last two decades. The results of the performed regression analysis of panel data suggest that trade liberalization has a quantitatively significant positive effect on growth. By using the coefficient estimates on tariff, the authors perform a quantitative evaluation of gains and losses from trade policy, for which tariff measures to trade （imports） are used as a proxy.

纵向资料回归系数的新估计

本文研究纵向资料中回归系数的估计，借助于相依回归模型中的信息迭加法，给出了一个新估计，它改进了最小二乘估计．

Weighted quantile regression for longitudinal data using empirical likelihood

This paper proposes a new weighted quantile regression model for longitudinal data with weights chosen by empirical likelihood(EL). This approach efficiently incorporates the information from the conditional quantile restrictions to account for within-subject correlations. The resulted estimate is computationally simple and has good performance under modest or high within-subject correlation. The efficiency gain is quantified theoretically and illustrated via simulation and a real data application.

SOME PROBLEMS AND TREATMENT IN THE REGRESSION ANALYSIS OF METEOROLOGICAL DATA

In this paper,some problems of regression analysis in the meteorological application are discussed and main reasons for statistical inference failures are analysed.We may find the failure problems with diagnos- tic method and solve them by different treatment.It has been proved that the treatment make the accuracy and stability of forecasting improved greatly.

INVERSE REGRESSION METHOD IN DATA STRUCTURE ANALYSIS

In order to explore the nonlinear structure hidden in high-dimensional data, some dimen-sion reduction techniques have been developed, such as the Projection Pursuit technique (PP).However, PP will involve enormous computational load. To overcome this, an inverse regressionmethod is proposed. In this paper, we discuss and develop this method. To seek the interestingprojective direction, the minimization of the residual sum of squares is used as a criterion, andspline functions are applied to approximate the general nonlinear transform function. The algo-rithm is simple, and saves the computational load. Under certain proper conditions, consistencyof the estimators of the interesting direction is shown.

Determinants of China’s OFDI Location Choices:A Comparison Study Between BRI Countries and Non-BRI Countries

In recent years,China’s outward foreign direct investment(OFDI)has risen significantly,arousing considerable interest in the motivations and drivers of Chinese overseas investment.This paper selected 27 host country-related indicators and extracted the common factors using the factor analysis method.This paper discusses the determinants of China’s OFDI location choice by using panel data regression method,and focuses on the differences between Belt and Road countries and nonBelt and Road countries.The results show that the favorable institutional environment and strong market demand of host countries have a positive influence on Chinese foreign investment.Besides,China’s investment in Belt and Road Initiative countries is more prone to a country with less developed technology and unreasonable energy utilization.China’s OFDI can promote technological progress in these countries and making full use of their advantage resources for economic development.As China’s economy has entered a“new normal”,its global influence has risen,and the relationship between the host countries and China has also mattered more on China’s OFDI decisions.This effort provides important supports for optimizing the location choices of Chinese enterprises’foreign investment.

On business cycle forecasting

We develop a recession forecasting framework using a less restrictive target variable and more flexible and inclusive specification than those used in the literature.The target variable captures the occurrence of a recession within a given future period rather than at a specific future point in time(widely used in the literature).The modeling specification combines an autoregressive Logit model capturing the autocorrelation of business cycles,a dynamic factor model encompassing many economic and financial variables,and a mixed data sampling regression incorporating common factors with mixed sampling frequencies.The model gene rates significantly more accurate forecasts for U.S.recessions with smaller forecast errors and stronger early signals for the turning points of business cycles than those gene rated by existing models.