關(guān)于農(nóng)村金融發(fā)展對(duì)經(jīng)濟(jì)發(fā)展影響的外文翻譯--農(nóng)村金融發(fā)展不會(huì)促進(jìn)經(jīng)濟(jì)發(fā)展嗎？-全文預(yù)覽
【正文】 t the national unemployment rate stood at percent in 2020 pared to % in 2020 and % in 2020 while the rate is higher in the rural area (%) than in the urban area (%). Poverty and unemployment in Nigeria are two sides of the same coin and could be linked to lack of adequate financial access particularly in the rural, among other things (Aliero, Ibrahim and Shuaibu, 2020). It has been argued that financial development has the capacity of reducing unemployment. It is along this line Dromel, Kolakez and Lehmann (2020) contend that development of private credit (which is a measure of financial development) would significantly lower unemployment persistence. This led Aliero and Ibrahim (2020) to predictably believed that enhancing access to formal financial services especially credit to the rural populace has not only have the capacity of reducing unemployment but also is a mean of reducing poverty in developing countries. Therecent breakthrough in the development finance emphasises that economic development of Less Developed Countries (LDCs) could be best achieved through bottomtop intervention principally due to duo reasons. Firstly, the vast majority of the populace of LDCs are dwelling in the rural areas while very small fractions are residing in the cities swimming within overwhelming quantity of national cake. Secondly, history shows that before LDCs opted for urbanisation programmes (topbottom intervention), development is steadily tricklingdown through the entire country paving the way for economic prosperity in simpler format. To my knowledge there is no any study ever conducted using time series techniques of data analysis on the relationship between rural financial sector development and economic growth. This study intends to fillin the lacuna by unveiling the role of rural financial development on the growth of Nigerian economy. In achieving this objective the paper is divided into five sections including this introduction. Section two presents the empirical literature. Section three contains the methodology of the study. Section four is the empirical result while the last section concludes the paper. 2 Methodology Time series secondary data for the relevant variables were sourced from CBN statistical bulletin of various issues, National Bureau of Statistics, International Financial Statistics (IFS) and World Development Indicators (WDI). The data covers 19802020 period and variables were expressed in their natural logarithm. Logarithmic transformations of variables are very popular in econometrics for a number of reasons。因此，可以毫無(wú)疑問(wèn)地認(rèn)為，正規(guī)信貸在農(nóng)村的股票可以作為金融發(fā) 展的最不發(fā)達(dá)國(guó)家 的代表。 沒(méi)有將一個(gè)國(guó)家的經(jīng)濟(jì)發(fā)展程度 作為 標(biāo)志的金融發(fā)展 的 研究必然會(huì)產(chǎn)生不同的結(jié)果?？紤]下面 p 階的 VAR 模型： ? ?2. .. .. . .. .. ..1 ttptpttt BxYAYAY ?????? ?? 其中 tY 是一個(gè) k矢量非平穩(wěn) I(1)變量， tX 是一個(gè) d 矢量 確定性變量，和 t? 是 創(chuàng)新的 變量 。在每一種情況下，零假設(shè)是對(duì)總體方案進(jìn)行測(cè)試。 然而，它不容許假設(shè)協(xié)整關(guān)系本身的測(cè)試。如果非平穩(wěn)的假設(shè)是成立的基本變量，它允許評(píng)估為共整合的關(guān)系。 一般來(lái)說(shuō)一個(gè)系列，即被 差分 n 次， n 階整合后并記為 I（ n） 。在 股票沃森動(dòng)態(tài) OLS模型能有效地估算長(zhǎng)期運(yùn)行參數(shù)，分析必須 和整合的 I（ 1）變量 中存在 協(xié)整關(guān)系。變量的對(duì)數(shù)變換是 在計(jì)量經(jīng)濟(jì)學(xué)是非常流行，原因是 ：首先許多經(jīng)濟(jì)時(shí)間序列數(shù)據(jù)表現(xiàn)出 強(qiáng)烈的趨勢(shì) ，其次，采取了一系列的自然對(duì)數(shù)線性化有效指數(shù)趨勢(shì)（如果有的話）的時(shí)間序列數(shù)據(jù)，因?yàn)閷?duì)數(shù)函數(shù)是一個(gè)指數(shù)函數(shù)（ Asteriou 和 Price， 2020年）的倒數(shù)。本研究 通過(guò)揭示 農(nóng)村金融發(fā)展對(duì)尼日利亞經(jīng)濟(jì)增長(zhǎng)中的作用 填補(bǔ)了空白。 在 金融發(fā)展突破中 強(qiáng)調(diào)，欠發(fā)達(dá)的國(guó)家（最不發(fā)達(dá) 國(guó)家）的經(jīng)濟(jì)發(fā)展可以通過(guò)自下到上的干預(yù)主要是由人 來(lái)實(shí)現(xiàn)。 （ Aliero， Ibrah
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