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https://github.com/mahnoorsheikh16/estimating-aggregate-import-demand-function

To test whether the economic theory for imports, real GDP and relative prices holds in real life scenario, this study analyses the extent of association between the variables through regression analysis. The paper can be used to assess the difference in impact of global events on GDP and import volume.
https://github.com/mahnoorsheikh16/estimating-aggregate-import-demand-function

autocorrelation breakpoint-detection chow-test correlation-analysis cross-sectional-data economics-models f-test imf-data log-log-graphs policy-analysis ramsay regression-analysis spss-statistics time-series-analysis wald-test

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To test whether the economic theory for imports, real GDP and relative prices holds in real life scenario, this study analyses the extent of association between the variables through regression analysis. The paper can be used to assess the difference in impact of global events on GDP and import volume.

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## Regression Analysis: Estimating Aggregate Import Demand Function

#### Introduction
Economic theory suggests a positive association between the growth of a country’s import volume and its real Gross Domestic Product (GDP) along with relative prices against other countries. This is evident from the likely increase in an economy’s demand for imported goods and services as their disposable income increase. Therefore, as GDP increases, meaning the value of domestic production increases, the expenditure on imports also elevates. Similar effect on the import volume of a country is carried by the increase in relative prices, considering that imported goods become relatively cheaper in comparison to local goods. Increase in either the real GDP or relative prices against any other country drives the overall demand for imports higher. This conventional economic theory is supported by various literatures, however, there is a need to test the economic theory in real-world situations.
To test whether the economic theory for imports, real GDP and relative prices holds in real-life scenario, this study will analyse the extent of association between the variables through a carefully developed econometric model. The analysis will be based on the dynamically varied economies of Pakistan, Brazil and China. The study will include relevance of global economic events i.e. the 2008 global financial crisis, to suspect the comparable impact of global economic turndowns on developing to developed countries. The paper can be used to assess the difference in impact of global events on GDP and import volume, along with lending evidence to the discussed conventional economic theory.

#### Data
The data for the countries is extracted from IMF (International Monetary Fund).
www.data.imf.org

#### Econometric Model
The econometric model utilizes income, relative prices and exchange rate volatility as explanatory variables. In relation to the conventional economic theory, the rise in
import volume with respect to either the rise in real GDP, exchange rate volatility or relative prices. Therefore, this econometric model dictates the positive association between aggregate demand for imports and the explanatory variables.

#### Methodology
For analysis of aggregate import demand function, I have used an extensive 47 years of data ranging from the years 1970 to 2016 inclusive for Pakistan, Brazil & China. A log-log model is utilized for developing the econometric model of imports, income (real GDP) and relative prices for the respective countries. The research paper consists of 3 different models for each country and contains income and relative prices as explanatory variables. For an in-depth analysis, both cross-sectional and time-series analysis have been carried out. Time series utilizes the three countries over 1970-2016. The cross sectional analysis tests the model for 2001 and 2014 to check significance for the impact on imports before and after the 2008 global financial crisis.
Further on, I have added quadratic terms to the models to reflect the practical behavior of the variables with respect to conventional economic theory. Moreover, statistical tests i.e. Wald Test, Global F-test and Ramsay Test are used to authenticate the specification of the model as well as the extent to which the explanatory variables fit the models. For correlation diagnostics, I have used serial correlation test, in order to identify the order of autocorrelation in our data. For breakpoint test for major economic event, the 2008 global financial crisis, I have used Chow Test to check if the parameters are significant pre and post the major economic events.

#### Results
Originally, Pakistan and Brazil showed a positive effect of both income and prices on imports but China showed a positive effect for income only. However, when volatility is also considered, both volatility and income increase imports if relative prices shifts. For Brazil, volatility affects import demand negatively, however, the effects of income and price remained unchanged. For China, volatility affects positively but the effect of other variables remains unchanged. Hence, the findings suggested that both Pakistan and China do not increase their imports as domestic prices elevate, rather their populations tend to reduce their imports. A significant similarity lies in reducing import expenditure as relative prices inflate for both developing and developed economies.

Considering the three economies (Pakistan, Brazil & China), it can be generalized that from developing to developed economies, the factors influencing import expenditure are altered as the economy develops. Hence, the impact of relative prices is subsided by other factors for highly developed economies. Thereby, lending the similarity in reduced impact on imports owing to rising domestic prices. For developed economies, other factors may include the significant proportion of imported goods being luxuries that can be avoided as domestic prices rise and purchasing power of locals’ falls. Whereas, for Pakistan, the heavy dependence on imports of necessities holds the econometric model true. Moreover, it is observed that exchange rate volatility affected developing and emerging economies more than developed economies owing to the revered effect of relative prices on developed countries.

Furthermore, with regards to major economic turndowns i.e. 2008 global financial crisis, it can be observed that prior to the event, only an increase in relative prices led to a rise in an economy’s expenditure on imports while rising carried a negative impact on imports. However, post-financial crisis statistics illustrated a turndown of the negative effect of income as an increase in both variables accentuated a rise in imports. The findings reciprocate a significant influence of the 2008 financial crisis on developed economies like China, whereas, it did not impact less stable economies like Pakistan and Brazil much significantly.