本文選題：交互效應 + 非線性平滑轉換��； 參考：《華中科技大學》2014年博士論文

【摘要】：傳統(tǒng)面板數據模型通常以可加形式引入個體效應和時間效應,來反映個體異質性與不隨個體變化的時間效應。Bai(2009)提出了交互效應的面板數據模型(IEPDM),在傳統(tǒng)面板數據模型中引入了個體效應與時間效應的交互項,來揭示共同因素對不同個體的效應差異性。近幾年來,帶交互效應的面板數據模型備受關注,其理論研究得到了深入發(fā)展。但現有的交互效應面板數據模型的研究都是基于二維面板數據結構,單方程的線性模型�；诙S面板數據結構模型無法研究區(qū)域間的勞動力流動、資本流動和雙邊貿易等實際案例；基于線性模型不能反映現實經濟中變量之間的非線性關系；基于單方程的交互效應面板數據模型無法考察變量間的反饋機制、動態(tài)沖擊效應。所以,在全面系統(tǒng)地分析現有交互效應面板數據模型的優(yōu)點基礎上,本文的研究內容分為兩個層次：一是模型方法論研究,二是方法論成果對中國現實問題的應用。 方法論研究：第一,鑒于線性模型無法考察經濟變量之間的非線性關系,本文將非線性平滑轉換引入到交互效應的面板數據模型中,建立了非線性交互效應面板數據模型(NIEPDM)。對靜態(tài)模型提出了非線性迭代OLS(NIOLS)估計；對動態(tài)模型構建了非線性迭代GMM(NIGMM)估計,兩類估計量均具有一致性。蒙特卡羅仿真結果顯示估計量的有限樣本性質良好。 第二,鑒于交互效應的單方程面板數據模型不能反映變量間的反饋機制,無法測度內生變量的沖擊效應,本文將交互效應擴展到了多方程的面板結構VAR(SVAR)領域,建立了帶交互效應的面板結構VAR(IEPSVAR)模型,并針對IEPSVAR模型給出了詳細的參數估計方法和估計程序。 第三,本文在傳統(tǒng)三維面板數據模型中引入了交互效應,建立了帶交互效應的三維面板數據模型,并對靜態(tài)模型提出了迭代OLS(IOLS)估計方法；對動態(tài)模型提出了迭代GMM(IGMM)估計方法。蒙特卡羅仿真實驗結果表明,有限樣本性質良好。 方法論成果對中國現實經濟問題的應用研究：為了對本文所介紹理論模型提供較完整的應用案例,本文分別對人口結構、信貸規(guī)模與房地產價格的趨勢調整；財政支出的自激勵機制、溢出效應與區(qū)域不平衡性；經濟地理分割與城鄉(xiāng)間產業(yè)轉移三個問題進行了實證研究。 第一,對人口結構、信貸規(guī)模與房地產價格的趨勢調整研究是基于非線性交互效應動態(tài)面板數據模型,借以評判中國社會經濟轉軌形態(tài)中人口結構對房價長期趨勢的影響以及貨幣工具在房價調控中的有效性和適用性。實證分析顯示：少年撫養(yǎng)比下降將對中國房價產生長期的抑制作用。老年撫養(yǎng)比上升對東部房價的抑制性開始顯現,但對中部暫時具有推動作用。伴隨著信貸擴張,東部房地產市場投機和泡沫化特征在2004-2007年間開始凸顯；2009年以后,投機性需求向西部地區(qū)轉移；中部投機性需求特征較不明顯。東部房地產價格對利率調整最敏感,具有近似單元彈性,西部地區(qū)的彈性約0.5左右,中部地區(qū)最不敏感。 第二,對財政支出的自激勵機制、溢出效應與區(qū)域不平衡性研究是基于交互效應的面板SVAR模型,系統(tǒng)分析財政支出對地區(qū)經濟運行效率的動態(tài)自激勵機制、溢出效應以及對區(qū)域平衡的調節(jié)功效。實證分析結果顯示：地方財政支出對經濟效率存在顯著的自激勵效應和溢出效應,但是與經驗判斷不同,中西部地區(qū)財政支出的溢出效應明顯強于東部地區(qū)。中央財政支出對經濟效率的激勵效應也存在顯著的地區(qū)差異,自東向西逐漸弱化。因而,增強欠發(fā)達地區(qū)自主的財政支出能力,是提高經濟運行效率、促進區(qū)域平衡發(fā)展的關鍵。 第三,對經濟地理分割與城鄉(xiāng)間產業(yè)轉移研究也是基于交互效應的面板SVAR模型。從經濟地理兩方面構建了城鄉(xiāng)產業(yè)轉移的理論框架和實證分析模型。其研究結果表明：在影響城鄉(xiāng)產業(yè)轉移的諸多因素中,產業(yè)基礎是最重要的決定因素。資本流動是最主要的引導力量,比勞動力流動更具導向性。地理差距對城鄉(xiāng)產業(yè)轉移的分割效應明顯大于收入差距。樣本期內,社會政策環(huán)境因素更有利于中西部地區(qū)城鄉(xiāng)間產業(yè)轉移,對經濟發(fā)達地區(qū)效應不明顯甚至有阻滯作用。
[Abstract]:The traditional panel data model usually introduces the individual effect and time effect in addition form to reflect the individual heterogeneity and the time effect that does not change with the individual.Bai (2009). The panel data model (IEPDM) of interaction effect is proposed. In the traditional panel data model, the interaction of the body effect and the time effect is introduced to reveal the common factors. In recent years, the panel data model with interaction effect has attracted much attention, and its theoretical research has been developed deeply. However, the existing interactive panel data models are based on the two-dimensional panel data structure and linear model of single equation. The base Yu Erwei panel data structure model can not be studied in the area. The actual cases of labor flow, capital flow and bilateral trade between regions; the linear model can not reflect the nonlinear relationship between the variables in the real economy, and the interaction effect panel data model based on single equation can not examine the feedback mechanism and dynamic impact effect between variables. Therefore, the existing interaction effect is systematically analyzed. On the basis of the advantages of the panel data model, the research content of this paper is divided into two levels: one is model methodology research, and the two is the application of methodology results to Chinese realistic problems.
Methodological research: first, in view of the inability of linear model to investigate the nonlinear relationship between economic variables, the nonlinear smooth transition is introduced into the panel data model of interactive effect, and the nonlinear interaction effect panel data model (NIEPDM) is established. The nonlinear iterative OLS (NIOLS) estimation is proposed for the static model, and the dynamic model is used for the dynamic model. The nonlinear iterative GMM (NIGMM) estimation is constructed, and the two kinds of estimators are consistent. Monte Carlo simulation results show that the finite sample property of the estimator is good.
Second, in view of the interaction effect single equation panel data model can not reflect the feedback mechanism between variables and can't measure the impact effect of endogenous variables, this paper extends the interaction effect to the panel structure VAR (SVAR) domain of multiple equations, and establishes a panel structure VAR (IEPSVAR) model with interaction effect, and gives a detailed description of the IEPSVAR model. A fine parameter estimation method and an estimator.
Third, in this paper, the interaction effect is introduced in the traditional 3D panel data model. A three-dimensional panel data model with interaction effects is established, and an iterative OLS (IOLS) estimation method is proposed for the static model. The iterative GMM (IGMM) estimation method is proposed for the dynamic model. The Mont Carlo simulation results show that the finite sample is of good properties.
The application of methodology results to China's real economic problems: in order to provide a more complete application case for the theoretical model introduced in this paper, the trend adjustment of population structure, credit scale and real estate price, self incentive mechanism of fiscal expenditure, spillover effect and regional imbalance; economic geography segmentation and urban and rural areas The three problems of inter industrial transfer are studied.
First, the research on the trend adjustment of population structure, credit scale and real estate price is based on the dynamic panel data model of nonlinear interaction effect, which is used to judge the effect of population structure on the long-term trend of housing price in China's social and economic transition form and the effectiveness and applicability of monetary instruments in house price regulation and control. The decline in the juvenile dependency ratio will have a long-term inhibitory effect on house prices in China. The inhibition of housing prices in the eastern part of the upbringing ratio began to appear, but it has a temporary effect on the central region. With the credit expansion, the characteristics of speculation and foam in the Eastern real estate market began to highlight in the 2004-2007 years; after 2009, speculative demand The western region transfer; the characteristics of the central speculative demand are not obvious. The Eastern real estate price is most sensitive to the interest rate adjustment, with approximate unit elasticity, about 0.5 in the western region, and the most insensitive in the central region.
Second, the research on the self incentive mechanism of fiscal expenditure, the study of spillover effect and regional imbalance is a panel SVAR model based on the interaction effect, and systematically analyzes the dynamic self incentive mechanism of fiscal expenditure on regional economic efficiency, the spillover effect and the regulation effect on the regional balance. There is significant self incentive effect and spillover effect in economic efficiency, but different from experience, the spillover effect of fiscal expenditure in the central and western regions is obviously stronger than that in the eastern region. The incentive effect of central fiscal expenditure on economic efficiency also has significant regional differences, which gradually weaken from east to west. Thus, the independent finance in the underdeveloped areas is strengthened. The ability to pay is the key to improving economic efficiency and promoting balanced regional development.
Third, the study of economic geography division and urban industrial transfer is also a panel SVAR model based on interaction effect. The theoretical framework and empirical analysis model of urban and rural industrial transfer are constructed from two aspects of economic geography. The results show that among the factors affecting the industrial transfer of urban and rural industries, the industrial base is the most important determinant. Capital flow is the main guiding force, which is more guiding than labor flow. The segmentation effect of geographical gap on urban and rural industrial transfer is obviously greater than income gap. In the sample period, social policy and environmental factors are more conducive to the transfer of urban and rural industry in the middle and western regions, and have no obvious or even block effect on the economic developed areas.
【學位授予單位】：華中科技大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：F224;F124

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