摘 要

近些年来，我国GDP的增长变得日益迅速，经济发展日新月异。几十年来，金融业发展的成果也同样令人瞩目。我国首都北京市和长江三角区核心城市上海市都是我国的一线城市，也是经济发达地区，也是国内金融业实力最高的地区。除了银行业和证券业，金融业的主要分支还包括了保险业，这三个产业的发展现状和前景可以反映出本国金融发展水平的高低，所以笔者选择了与这三个产业相关的指标来研究金融业的发展。在过去的学术研究中，经济增长与金融发展之间的联系向来被各行各业的学者和专业人士关注，不仅如此，我国的第三产业日益兴盛，随之而来的是对金融业发展水平的高度关注。因此，研究GDP增长与金融发展之间的各种联系将更加具有实际意义。

本文选取北京市和上海市1998-2017年的年度数据，研究人均GDP与融相关率、证券化率和保险深度之间的联系。本文首先选取多元回归模型对二者之间的联系进行概述，又选取了格兰杰因果检验和面板数据模型使研究更为准确。多元回归模型结果表明北京市的金融包含的几个指标的发展对本市GDP的增长的作用都是正效应，金融发展大体上可以促进本市GDP的增长。格兰杰因果关系检验结论表明，北京市的金融相关率的增长是GDP增长的原因，北京市银行业的发展可以推进北京市GDP的增长，但是证券和保险却不是经济增长的原因；上海市金融相关率和证券化率的增长是GDP增长的格兰杰原因，上海市的银行和证券的进步都可以促进上海市GDP的增长，而保险业却与经济增长没有明确的因果联系。面板数据模型实证研究结果表明，金融业的主要分支产业的繁荣发展能够推进GDP的增长，对GDP的增长是正效应；模型还显示上海市的金融发展环境比北京市略好；且随着时间的前进，地区金融业的发展推动地区经济增长的正效应愈加明显。

最后结合研究结果，本文对研究结论进行了总结并针对结论提出了相应的政策建议，总体来说，要继续鼓励金融业的发展以促进GDP的增长，完善金融结构，加强金融业的管理，使金融业的管理制度更为健全和完善。

关键词：GDP增长；金融相关率；格兰杰因果检验；面板模型；

Abstract

In recent years, China's GDP growth has become increasingly rapid, and economic development is changing with each passing day. The results of the development of the financial industry have also been remarkable for decades. China's capital Beijing and the core city of the Yangtze River Delta are Shanghai's first-tier cities, economically developed regions, and the region with the highest strength in the domestic financial industry. In addition to the banking and securities industries, the main branches of the financial industry also include the insurance industry. The development status and prospects of these three industries can reflect the level of financial development in the country. Therefore, the author has chosen indicators related to these three industries. Study the development of the financial industry. In the past academic research, the link between economic growth and financial development has always been concerned by scholars and professionals from all walks of life. Not only that, but China’s tertiary industry is booming, and it is followed by the development level of the financial industry. Highly concerned. Therefore, studying the various links between GDP growth and financial development will be more practical.

This paper selects the annual data of Beijing and Shanghai from 1998 to 2017 to study the relationship between per capita GDP and the correlation rate, securitization rate and insurance depth. This paper first selects the multivariate regression model to summarize the relationship between the two, and selects the Granger causality test and the panel data model to make the research more accurate. The results of multiple regression models show that the development of several indicators included in Beijing's financial sector has a positive effect on the growth of GDP in this city. Financial development can generally promote the growth of GDP in this city. The results of Granger causality test show that the growth of financial correlation rate in Beijing is the cause of GDP growth. The development of Beijing's banking industry can promote the growth of Beijing's GDP, but securities and insurance are not the cause of economic growth; Shanghai The growth of financial correlation rate and securitization rate is the Granger cause of GDP growth. The progress of Shanghai's banks and securities can promote the growth of Shanghai's GDP, while the insurance industry has no clear causal link with economic growth. The empirical results of the panel data model show that the prosperity of the main branches of the financial industry can promote GDP growth and positive effects on GDP growth; the model also shows that Shanghai's financial development environment is slightly better than Beijing; and over time Advancing, the positive effects of regional financial industry's development to promote regional economic growth have become more apparent.

Finally, combined with the research results, this paper summarizes the research conclusions and puts forward corresponding policy recommendations for the conclusions. In general, we must continue to encourage the development of the financial industry to promote GDP growth, improve the financial structure, and strengthen the management of the financial industry. The management system of the financial industry is more complete and perfect.

Key words: GDP growth; financial correlation rate; Granger causality test; panel model;

目 录

第1章 绪论 1

1.1 引言 1

1.2 本文的研究背景及意义 1

1.3 国内外研究现状 2

1.4 北京和上海GDP增长与金融发展现状 3

1.5 本文的研究思路、组织结构及创新点 4

1.5.1 本文的研究思路 4

1.5.2 本文的主要研究内容 4

1.5.3 本文的创新点 4

第2章 研究的相关基础知识 6

2.1 多元回归模型 6

2.1.1 多元线性回归模型的一般形式 6

2.1.2 回归方程的显著性检验 6

2.1.3 拟合优度 6

2.2 ADF单位根检验 6

2.3 协整检验 8

2.3.1 协整的概念 8

2.3.2 恩格尔-格兰杰法协整检验 8

2.4 格兰杰因果关系检验 8

2.5 面板数据模型 9

第3章 GDP与金融指标序列的协整检验 10

3.1 实证研究概述 10

3.1.1 实证方法的选取 10

3.1.2 指标的选取 10

3.1.3 数据的选取 10

3.1.4 北京市经济发展与金融发展概况 10

3.1.4.1 北京市经济发展概况 11

3.1.4.2 北京市金融发展概况 11

3.2 北京市GDP与金融指标的多元线性回归模型 13

3.2.1 模型的建立 13

3.2.2 模型的显著性检验 14

3.3 GDP与金融指标序列的ADF单位根检验 15

3.3.1 北京市GDP与金融指标序列的ADF单位根检验 15

3.3.2 上海市GDP与金融指标序列的ADF单位根检验 17

3.4 GDP与金融指标序列的协整检验 19

3.4.1 北京市GDP与金融指标序列的协整检验 19

3.4.2 上海市GDP与金融指标序列的协整检验 20

第4章 GDP增长与金融发展的格兰杰因果检验和面板模型 22

4.1 北京市和上海市GDP增长与金融发展的格兰杰因果检验 22

4.1.1 北京市GDP增长与金融发展的格兰杰因果检验 22

4.1.2 上海市GDP增长与金融发展的格兰杰因果检验 22

4.2 GDP与金融指标的面板数据模型 23

4.2.1 北京市和上海市金融发展的GDP增长效应 23

4.2.2 北京市和上海市金融发展对GDP增长的区域效应 24

4.2.3 北京市和上海市金融发展对GDP增长的时间趋势效应 24

第5章 结论与建议 26

5.1 研究结论 26

5.2 政策与建议 27