Hello,
I need help with part of a financial Econometrics empirical project paper. There are guidelines you MUST follow and I have put things in great detail. Feel free to ask any questions.
The hypothesis of this paper is testing whether standard errors are prevalent with our economy’s variables like trade, economic growth, inflation, unemployment, interest rates, and mortgage rates.
You will be provided two papers to help base your writing on but PLEASE make sure to search for more papers from accredited sources.
You are responsible for two sections of the paper:
1)Introduction/Motivation
2)Literature Review
You are not supposed to do the other sections but keep them in mind so our work here flows seamlessly into what my groupmates are doing. Below is a breakdown of these sections:
1. Introduction/Motivation
Here is the place to lay out explicitly:
3) What is your contribution? How are you answering the question? You should state whether you are testing a model, evaluating a program or a change in policy, and what data you are using. 4) What are your main results? Explain briefly how your findings differ from previous work and what the implications of these findings are. If your analysis is inconclusive (which is fine!) be upfront about this and very briefly state why.
2. Literature Review
This section should basically consist of two parts (both of which should be brief).
I WILL PROVIDE A MAJORITY OF THE DATA AND SUCH THAT MY GROUPMATES MADE, WHICH HELPS CREATE THE NEXT SECTIONS OF THE PAPER, SO THAT YOUR SECTIONS OF THE PAPER ARE BETTER INFORMED.
Here is a breakdown of the documents attached:
1) Analyzing the Relationship Between Trade and Economic Growth Base Paper – a base paper to help you write the first and 2nd sections of this paper
2) Estimating Standard Errors Base Paper- a base paper to help you write the first and 2nd sections of this paper
3) Empirical Project How to Write – A longer explanation of how the paper is structured
4) Empirical Project Paper Guide- A shorter explanation of how the paper is structured
5)Initial Data- This data is what is used to create sections 3-5 of the rest of the paper, and can help inform your writing as to what’s coming later in the paper.6)Data for empirical project- This is the data my groupmates will build this project’s model on. It has various economic datasets (GDP, unemployment, mortgage rate, inflation) wherein they will find the correlation between each point with each other and also all well points together and can help predict some value. All this data is from the U.S’s FRED (Federal Reserve Economic Data)
https://fred.stlouisfed.org/
Relationship between Trade and Economic Growth
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Analyzing the Relationship Between Trade and Economic Growth
Carly Schmitt, Nicole Imhof, Tal Nechmad
November 21, 2019
ECON 3161: Econometric Analysis
Dr. Shatakshee Dhongde
Abstract
This paper examines how a country’s amount of total trade spurs economic growth within countries. The
paper will analyze how the total trade activity, measured as the combined level of exports and imports,
impacts economic growth, measured as changes in GDP per capita. The model is expanded to include a
country’s amount of foreign direct investment, gross savings, unemployment level, amount of
manufacturing in the economy, and the country’s overall status as a developed or developing economy as
other potential factors and influencers of economic growth. The final model indicates that the most
important influencers of economic growth are foreign investment, savings, unemployment, and the
country’s development level.
Relationship between Trade and Economic Growth
I.
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Introduction
The export-led growth hypothesis (ELGH) within economic theory, as defined by Emilio Medina
Smith (2001), claims that any increase in exports drives the growth of a country and spurs economic
development. The ELGH guided the underlying rationale of this paper, that economic growth is
dependent on the amount of trade within a country, and aided the choice in variables. While the
hypothesis focuses specifically on exports, total trade activity may be a better indication of participation
in the global economy as it more fully reflects a nation’s international cooperation. The relationship
between economic growth and a country’s total trade is important for policy makers to understand how to
stimulate growth. Domestic trade policies often oscillates between protectionism, the defense of national
industries, and trade liberalization, the opening of markets and encouragement of free trade throughout
the world. Investigating the impact of total trade on economic growth is crucial for developing trade
policies that will grow an economy continuously and efficiently. Considering how the amount of trade,
foreign direct investment, and savings impact economic growth provides a well-rounded picture for
policy makers to consider when establishing international trade policy. As globalization permeates into
the lives of every consumer and into every country, identifying what spurs domestic economic growth is
vital for increasing a country’s production and influence on the global stage.
The hypothesis behind the simple regression in this paper, which analyzes the impact that trade
volume has on economic growth, is that as a country’s total trade increases, GDP per capita will increase,
indicating economic growth. This hypothesized positive relationship is based on the ELGH and the
underlying notion that trade promotes production and therefore overall economic growth. The expanded
multiple linear regression predicts that in addition to total trade, increases in investment, savings, and
manufacturing will also increase GDP per capita. The model further hypothesizes that increased
unemployment levels will negatively relate to GDP per capita and that economies considered to already
be “developed economies” will be positively impacted more by trade, with higher GDP per capita.
II.
Literature Review
The relationship between trade and economic growth has often been supported by the premise
that increased trade liberalization in the modern, globalized world will encourage economic growth. This
paper attempts to uncover the most basic relationship between a country’s quantity of trade activity, a
subsector of globalization and indicator of trade liberalization, along with productivity factors as they
impact economic growth. Previous literature has defined trade liberalization in a wide range of ways.
Often, studies attempt to utilize pre-established indexes as a measure of trade liberalization in a nation’s
economy. The differences in definition have led to varied results and little consensus.
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A survey of several models of the causal relationship between international trade and economic
growth done by Tarlok Singh (2010) found inconsistent trends of data analysis and collection surrounding
international trade impacts. In both micro- and macroeconomic settings, it is nearly impossible to
untangle the web of data in such a way that provides for conclusive and repeated results. Those that focus
on microeconomic growth, where the productivity of a country is the direct correlation of variables that
range from research and development to infrastructure, have equally varied data to that of the
macroeconomic studies. The wide range of variables considered in the survey led Singh (2010) to
conclude that the inconsistencies of the data across the literature make it nearly impossible to find
common causal interpretations between various papers. For this reason, the model below is more narrow
in scope. A targeted examination of trade and trade’s impact on economic growth should reach a
conclusion that takes into account the investment that enters a country. As previous literature focused on
the impact of barriers to trade as a factor which affects economic growth, Singh’s (2010) findings that
Member States of the World Trade Organization (WTO) have not seen any more or less benefits from
trade than external states cast doubt on the importance of including politically motivated groups which is
why economic investment in the domestic economy has been determined to be more fundamental in a
country’s economic growth for the purposes of this study.
There is little argument that trade liberalization has a number of theoretical impacts on any given
economy. In theory, there is improvement of welfare, increased inflow of foreign direct investment (FDI),
a reduction in trade costs, increased international political cooperation, and the incentivization of global
stability. The reality found in the measurement of these outcomes is scattered at best. Sèna Kimm
Gnangnon (2018) assessed the impact of multilateral trade liberalization on countries’ economic growth
rates. Gnangnon (2018) utilized an index to define trade liberalization. The correlation pattern was
apparent between the multilateral trade liberalization index, measured at the Heritage Foundation’s
freedom of international trade index which examines domestic trade policy, and income growth rates.
Notably, the promotion of FDI inflows has a theoretical long term and short term impact on the economy
and it is this impact that produced interest in this model. The promotion and explanation of the domestic
industries and labor force played into the decision to include both savings and FDI into the new model
created below. Gnangnon (2018) found varied impact of trade liberalization based on country income and
concluded broadly that the countries already in a better position to accept trade liberalization policies
would further benefit from such measures.
In a study done by Shiva S. Makki and Agapi Somwaru (2004), the effects that FDI and trade
have on economic growth in developing countries are examined as an indicator of the success of
globalization. Trade, along with FDI, is thus a predicted channel of globalization and its integration with
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modern technology creates an incredibly important formula for economic growth worldwide. In this
literature piece, trade is defined as the sum of imports and exports as a percentage of GDP, which helped
formulate how trade would be defined in this paper. Makki and Somwaru (2018) strived to produce
results to show that trade and FDI work in tandem to promote economic growth. This hypothesis implies
that in order for trade to develop and for FDI to drive economic growth, and therefore to actually have
some benefit for a developing economy, there must be strong institutions and macroeconomic policies in
place. The model goes to show that trade and FDI did positively impact economic growth but neither
variable was statistically significant, implying that there may be other variables playing a larger role in
determining the magnitude of economic growth within a developing economy. The findings within this
literature helped to shape the thought process of this new study and help predict potential outcomes for
economic growth in relation to foreign investment and the level of trade within a country.
The model created by this new study brings together elements from many previous models that
attempted to find a causal relationship between trade and economic growth. Adding to the complex and
ever changing bank of literature on the relationship between trade and economic growth, this paper
controls for trade by including domestic investment and savings in an attempt to isolate the effects of
trade on economic growth. It similarly accounts for other domestic factors. This paper will include
controls for unemployment level, the percentage of trade involved in manufacturing, and whether or not
the country is considered to be a developed economy as a means of truly identifying what is the most
important factor for economic growth. In the wide realm of trade related economic analysis, the refreshed
focus attempts to bring together new ideas and previous findings as the economists chip away to
determine the most impactful variables which affect economic growth.
III.
Data
While there are seemingly infinite factors that may affect economic growth, the ELGH indicates
that trade, specifically exports, drive economic growth. A brief review of the literature indicates that this
is a diluted analysis, failing to account for wider global economic participation. Attempting to expand the
analysis of globalization’s impact on an individual economies, we have chosen to focus on the total
amount of trade and its relationship to economic growth. To measure economic growth, the dependent
variable used is GDP per capita, regressed as the log of GDP per capita in the models. We chose to take
the log of GDP per capita because it was a more normal distribution than just GDP per capita and would
fit better with our data. This is shown in Figure 1, the scatter plot with GDP per capita and Trade, and
comparing it to Figure 2, the scatterplot of log(GDP) per capita and Trade.
Relationship between Trade and Economic Growth
Figure 1
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Figure 2
The independent variable in our initial simple regression is trade. Trade is measured as the sum of
the imports and exports of goods and services as a percentage of a country’s GDP. This measurement was
chosen over a country’s level of trade, that is exports minus imports, because it reveals the total amount of
trade a country is involved in, rather than just their trade balance. Based on the literature, we created this
simple model to test that a positive relationship existed between trade activity and economic growth.
Additional variables were included in the multiple linear regression to better determine what
impacts economic growth and to decrease any omitted variable bias. The first variables added explored
the levels of investment and savings within a country. The investment variable is reported as foreign
direct investment, measured as the sum of the net inflows of equity capital, reinvestment of earnings, and
other long term capital as a percentage of GDP. It was determined that net inflows are better than net
outflows when determining economic growth as incoming FDI is a direct investment into a country’s
economy. Savings is calculated as the difference between disposable income and consumption plus net
transfers, also measured as a percentage of GDP. Later multiple linear regression analyses accounted for
unemployment and manufacturing as well. Unemployment is calculated as a percentage of the total labor
force that is without work but available and seeking employment. The manufacturing variable is measured
as value added to trade within the manufacturing sector, as a percentage of GDP. This is calculated by
adding up all the net outputs of those industries and subtracting the immediate inputs. The last
independent variable is a dummy variable that assigned 1 to developed countries, as reported by the
United Nations, and 0 to countries with developing economies and economies in transition. This variable
was added to control for more intangible differences in economies such as differences in infrastructure
and political circumstances which affect economic growth.
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All of the data for this research was gathered from the World Bank database and the United
Nations. The interpretation and source of all of the variables used can be seen in Figure 3. All data used
was reported for 2017 with 125 country observations used in this analysis; they are listed in the Appendix.
Figure 4 provides descriptive statistics for each of the variables used in the regression model.
Figure 3
Variable
Interpretation
Source
logGDP
Percent of GDP per capita as a measure of economic
World Bank
growth
Trade
Sum of exports and imports of goods and services as a
World Bank
percentage of a nation’s GDP
Investment
FDI measured by the sum of the net inflows of equity
World Bank
capital, reinvestment of earnings, and other long term
capital as a percentage of GDP
Savings
Difference between disposable income and consumption,
World Bank
including net transfers
Unemployment
Unemployment rate measured as a percentage of the total
World Bank
labor force
Manufacturing
Net output of the manufacturing sector after adding up
World Bank
all outputs minus intermediate inputs as a percentage of
GDP
Developed
Takes the value of 1 if a nation’s economy is considered
United Nations
developed by the UN and 0 if considered developing or
an economy in transition
As seen below in Figure 4, for the variables of trade, investment, savings, unemployment, and
manufacturing, there are quite large standard deviations, indicating that the mean may not be the best
value to use to determine the average. This may be caused by large outliers who have an abnormal
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amount of trade, investment, or savings in their nation such as the United States, which alone accounts for
over 30% of the world’s trade volume.
Figure 4
Variable
Mean
Standard Deviation
Minimum
Maximum
logGDP
3.80
0.622
2.55
5.02
Trade
88.49
56.01
24.14
412.87
Investment
4.17
6.80
-10.91
49.76
Savings
22.22
11.57
-48.78
55.64
Unemployment
6.61
4.93
0.14
27.33
Manufacturing
13.20
6.48
1.00
37.28
Developed
0.26
0.44
0.00
1.00
In Figure 2 (above), which depicts the scatter plot for log(GDP) and trade, there are some
instances where the amount of trade as a percent of GDP exceeds 100%, such as Luxembourg and
Singapore. This can be accredited to nations who participate in large volumes of trade relative to their
internal production levels. Countries who serve as entrepot hubs, where goods are processed without any
duties or additional packaging, or countries who export in one highly profitable sector may have higher
than average trade totals due to the nature of their trade relationships. The nations with the smallest
percentages of GDP are developing countries like Brazil, Argentina, and Pakistan. Since these are
countries that are developing, they have small amounts of trade as they don’t interact as much with other,
more developed nations. The other obvious outlier, where trade is 200 and log(GDP) is around 3.3, is
Vietnam. This is an interesting outlier as Vietnam is classified as a developing nation by the United
Nations but it participates in a large amount of trade compared to other developing nations.
Before running a regression analysis on the data, we must check to determine if it fits the
Gauss-Markov Assumptions, used for the multiple linear regressions, and the analogous assumptions for
the simple linear regression. Assumption SLR.1 states that the model is linear in parameters. This can be
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shown by the simple linear regression equation and determines that the x and y values have a linear
relationship, expressed in the below equation.
y=
β0 + β1x + u
Our model meets this condition because there is a linear relationship between GDP per capita and total
trade, our dependent and independent variables, respectively.
Assumption SLR.2 states that the data is a random sample drawn from the population. The model
meets this condition as the World Bank and the United Nations are trusted sources for data and data
analysis. Additionally, the large sample size of 125 countries ensures that the model is accounting for
countries with a wide range of incomes, resources, and specializations.
Assumption SLR.3 states that there is standard deviation in the dependent variable, meaning the
dependent variable values vary. The data fits this assumption since economic growth, measured as GDP
per capita, is different for each country. Assumption SLR.3 is written as follows:
∑(xi−x)2 >0.
Assumption SLR.4 is the zero conditional mean assumption. The zero conditional mean is written
below and says that the value of the dependent variable cannot contain any information about the value of
the unobserved factor, u.
E(ui | xi) = 0 .
As expected, the model does not meet this assumption. The unobserved factor does contain information
about the dependent variable since the simple linear regression could not possibly account for the array of
factors which influence GDP per capita. This is expected as it is extremely rare for all of the information
to be captured in one independent variable and one relationship.
Since the model does not meet the first four assumptions, it cannot be said that these are unbiased
estimators. However, running the simple linear regression will still indicate the relationship between GDP
per capita and the total trade but it will simply overestimate or underestimate the relationship.
Lastly, SLR.5 assumes homoskedasticity. This states that the dependent variable cannot contain
any information about the variability of the unobserved factors, written as:
Var( ui | xi)= σ2.
Homoskedasticity can be assumed for this model because it is likely that the values of the variance are
constant for the unobserved factors.
The multiple linear regression must also meet the Gauss-Markov assumptions. Assumptions
MLR.1 and MLR.2 are the same as SLR.1 and SLR.2, respectively, so the reasonings above can be
applied here as well. MLR.3 states that there is no perfect collinearity between any of the independent
variables. Figure 5 shows that there is no perfect collinearity between any of the variables nor are there
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any highly correlated variables. All of these results are taken from STATA and the output can be seen in
the Appendix.
Figure 5
Trade
Investment
Savings
Unemployment
Manufacturing
Trade
1.00
Investment
0.30
1.00
Savings
0.12
-0.06
1.00
Unemployment
-0.03
0.03
-0.15
1.00
Manufacturing
0.09
-0.10
0.34
-0.11
1.00
Developed
0.36
0.09
0.11
0.07
0.11
Developed
1.00
MLR.4 is the same as SLR.4, the zero conditional mean assumption. However, it can now be
expressed as the following equation for a multiple linear regression:
E(u i | x i1 , xi 2 ,…,
xik ) = 0.
The addition of independent variables means less information is contained within the unobserved factor,
u. The model is still likely to have bias but including more independent variables narrows the margin of
error and makes the estimates more accurate.
Lastly, MLR.5, like SLR.5, assumes homoskedasticity. Once again, the assumption is made for
this model because it is likely that the values of variance are constant for the unobserved factors.
IV.
Results
The simple linear regression of the log of GDP per capita and trade shows a statistically
significant, positive relationship between economic growth and total trade. Below is the econometric
equation for the simple linear regression model:
logGDP = 3.445 + 0.004(Trade)
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The simple linear regression shows that as the amount of trade as a percent of GDP increases by 1%, a
country’s GDP per capita will increase by 0.4%. While the coefficient is small, this may be explained by
the small range of logGDP. Further, the relationship between amount of trade and GDP per capita is
positive, aligning with the hypothesis developed based on a review of the literature. The regression
directly explains approximately 13% of the data, indicated by an R-squared value of 0.13.
The first multiple linear regression was developed to account for domestic savings and investment
into a country’s economy, an influential factor of economic output, widely accepted in economic theory.
The STATA results can be seen in the Appendix. The econometric equation is:
logGDP = 3.122 + 0.004(Trade) – 0.003(Investment) + 0.016(Savings)
The regression reflected the anticipated positive relationship between trade and GDP per capita and
savings and GDP per capita. Ceteris paribus, a 1% increase in trade results in a 0.4% increase in GDP per
capita and a 1% increase in savings results in a 1.6% increase in GDP per capita. Contrary to what the
literature suggested, a 1% increase in investment (FDI) resulted in a 0.3% decrease in GDP per capita.
The negative relationship between investment and economic growth is economically counterintuitive and
contrary to the literature. The relationship between these independent variables and the economic growth
indicator variable explains 22% of the data based on the R-squared value of 0.22. While including savings
and investment incorporated more data into the model, the low R-squared and unexpected negative
relationship required the multiple linear regression model to be expanded further.
The second multiple linear regression attempted to account for more sectors of the domestic
economy to better develop and explain the relationship between trade and economic growth. The
variables unemployment, manufacturing, and developed were added to create the following econometric
equation:
logGDP = 2.905 +0.001(Trade) – 0.002(Investment) +
0.013(Savings)+0.021(Unemployment)+0.010(Manufacturing)+0.813(Developed)
This second multiple linear regression, like the first, demonstrated positive relationships between all
variables except investment, which once again showed a negative correlation with GDP per capita. All of
the variables had small coefficients, demonstrating relatively flat linear relationships. The model shows
that as trade increases by 1%, GDP per capita increases by only 0.1%. Similarly small, as investment
increases by 1%, GDP per capita decreases by 0.2%. The model shows that as unemployment and
manufacturing each increase by 1%, GDP per capita will increase by 2.1% and 1%, respectively. The
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positive relationship between GDP per capita and unemployment did not align with the original
hypothesis and appears to be economically counterintuitive. The model indicates that developed countries
have an 81.3% overall increased GDP per capita. Of these variables, savings, unemployment, and
developed were all significant at the 1% level while trade was significant at the 10% level. The
investment and manufacturing variables were not significant in this regression. This multiple linear
regression did better in explaining the model than the first multiple linear regression. In this instance, 56%
of the data was explained as seen by the R-squared value of 0.56.
The second multiple linear regression variables did not explain economic growth with enough
significance to be a final model. Due to the high multicollinearity between several variables including
manufacturing and savings and trade and developed, joint significance tests were conducted to establish
the importance of these variables. Details of the joint significance tests can be found below in the
Extensions section.
The third multiple linear regression, seen below, removes the trade and manufacturing variables:
logGDP = 3.084+ 0.0004(Investment)+0.016(Savings)+0.019(Unemployment)+0.883(Developed)
In this model, only investment, savings, unemployment level, and developed are included as indicators of
economic growth. All of the coefficients associated with these variables correlate with the original
prediction, except for unemployment, that these effects would have a positive influence on economic
growth within a country. The model shows that as investment increases by 1%, GDP per capita increases
by 0.04%, a small but positive correlation. As savings increases by 1%, GDP per capita increases by
1.6%, similar to the first multiple linear regression model. A 1% increase in unemployment results in a
1.9% increase in GDP per capita; this positive relationship again seems to be counterintuitive. According
to the model, developed countries have a GDP per capita that is greater by 88.3%. This final model
explains 54% of the data, shown by the R-squared of .54.
The removal of the initial variable of interest serves to indicate the relatively low value of trade as
it relates to the growth of an economy. If anything, the strong correlation between developed and trade
indicates that trade is the result of an already mature economy that has previously experienced significant
growth over an explanatory factor for economic growth today.
A summary table is provided below in Figure 6 of all of the regressions, simple and multiple. The
table lists the coefficients of each variable, the associated standard error, the R-squared and adjusted
R-squared, and indicates whether or not the variable holds any significance.
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Figure 6
Variable
SLR
MLR I
MLR II
Trade
0.00399***
0.00368***
0.00136*
(0.000934)
(0.000942)
(0.000764)
-0.00276
-0.00185
0.000389
(0.00772)
(0.00590)
(0.00571)
0.0163***
0.0139***
0.0162***
(0.00436)
(0.00353)
(0.00340)
0.0207***
0.0191**
(0.00785)
(0.00794)
Investment
Savings
Unemployment
Manufacturing
MLR III
0.00964
(0.00628)
Developed
_cons
0.813***
0.883***
(0.0937)
(0.0892)
3.445***
3.122***
2.905***
3.084***
(0.0978)
(0.129)
(0.131)
(0.109)
R-squared
0.129
0.222
0.562
0.540
Adj. R-squared
0.122
0.202
0.539
0.525
Values in parentheses represent standard error
Significant at:
*10%, **5%, ***1%
As seen in Figure 6, in the final multiple regression model, the two variables savings and
developed are significant at the 1% level and one variable, unemployment, is significant at the 5% level.
The statistical significance of these variables can be proven using a t-test, p-values, and confidence
intervals. The corresponding t-values, p-values, and 95% confidence intervals are listed below for the
third multiple linear regression model. All of the data in Figure 7 was provided by the STATA output for
MLR III, which is located in the Appendix.
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Figure 7
Variable
Coefficient
t-value
p-value
(Standard Error)
Investment
0.0004
95% Confidence
Interval
0.07
0.946
(-0.011, 0.012)
4.77
0.000
(0.0095, 0.023)
2.40
0.018
(0.0034, 0.0348)
9.90
0.000
(0.706, 1.060)
(0.0057)
Savings
0.0162
(0.0034)
Unemployment
0.019
(0.0079)
Developed
0.883
(0.089)
The following hypothesis test will be used to test the significance of each variable in MLR III,
where βk represents
all of the independent variables, β1 through
β4.
H0: βk = 0
H1: βk ≠ 0
Using the t-values of each independent variable in MLR III, seen above in Figure 7, the
significance of each variable can be determined by performing a t-test. The t-test compares the t-value and
the critical value of the t-distribution. Two-tailed t-tests are used as the objective is to determine whether
or not the coefficient of each variable is significantly different from zero, without regard for whether it is
a positive or negative value. With 125 observations, there are 120 degrees of freedom for all of the t-tests.
The critical value for a two-tailed t-test with 120 degrees of freedom at a significance level of 1% is
2.617. If the absolute value of the t-value is greater than the critical value at any specific significance
level, then the null hypothesis can be rejected, indicating that the variable is statistically significant and
different than zero. At the 1% level, the variables savings and developed are significant because their
t-values are greater than the critical value. For a 5% significance level, the critical value for a two-tailed
t-test with 120 degrees of freedom, is 1.980. As seen in Figure 7, the t-value for the variable
unemployment is greater than this critical value, but less than the critical value at the 1% significance
level, which implies that unemployment is significant at 5% but not 1%. The last variable in MLR III,
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investment, is not significant at any level because its t-value is so low that it is not greater than any critical
value at any significance level (10%, 5%, or 1%).
The same hypothesis can be tested using p-values as well. The p-values for each independent
variable are also included in Figure 7. The p-value is the smallest level at which the null hypothesis is
rejected. The p-values for savings and developed are 0.000. Since these p-values are less than 0.01, which
corresponds to a 1% significance level, the p-values support the statistical significance that was proven
using the t-test, namely that the variables savings and developed are significant at the 1% significance
level. The p-value for unemployment is 0.018, which is between 0.01 and 0.05, and implies that the
minimum rejection level is 1.8%. The variable unemployment is therefore not significant at 1% but is
significant at 5%. The variable investment has a large p-value of 0.946, which supports the earlier t-test
conclusion that investment is not significant at any level of significance.
A third test of our hypothesis can be proven using 95% confidence intervals. The 95% confidence
intervals for the independent variables in MLR III can also be seen in Figure 7. A 95% confidence
interval implies that there is a 5% chance the coefficient of the variable lies outside of the confidence
interval. If zero is within the confidence interval, then it is inferred that the null hypothesis fails to be
rejected and the coefficient is not necessarily significantly different than zero. Of the variables in MLR
III, zero does not lie in the interval of the variables savings, developed, and unemployment, which shows
that all of the associated coefficients are significantly different than zero at a 5% significance level. The
null hypothesis that the coefficient is equal to zero can therefore be rejected for these three variables.
V.
Extensions
As the models in this paper expanded from the simple linear regression model, we sought to
identify more explanatory variables that would help better explain the dependent variable. In order to do
that, we chose to add a dummy variable to control for whether or not the country was considered
developed or developing. The addition of this dummy variable increased our R-squared significantly since
the model began to control for the difference in country categories, whether it be developed or
developing. Depending on which category the country is in will determine how large of an effect savings,
investment, and trade will have on GDP per capita and therefore on economic growth.
Removing the variables trade and manufacturing as independent variables in MLR III was
decided after performing F-tests on the joint significance of the collinearity between trade and developed
and between manufacturing and savings. The decision to test the collinearity between these two sets of
variables was due to the fact that these sets of variables had two of the highest collinearity coefficients,
which can be seen in Figure 5.
Relationship between Trade and Economic Growth
Group 9
To calculate the F-value for the joint significance test between trade and developed, we need to
create an unrestricted model that includes all of the variables within MLR II and a restricted model that
does not include either trade or savings. To test whether or not trade and developed are jointly significant,
we will use the following hypothesis test:
H0: β1 = β6 = 0
H1: H0 is not true
To calculate the F-value, we will use the calculation with the R-squared values of the restricted and
unrestricted models. The R-squared of the restricted model is 0.1883 and the R-squared of the unrestricted
model is 0.5616. The below calculation shows the F-value for trade and developed:
2
F = [(R2 ur
/ [(1−R2 ur
)/(n−k−1)]
– R r )/q]
F=
[(0.5616-0.1883)/2] / [(1-0.5616)/118)] = (0.1867)/(0.0037) = 50.446
This calculated F-value is much larger than the associated critical value, which is 3.07 for a test that has a
numerator degrees of freedom equal to 2 and a denominator degrees of freedom equal to 118. Since the
F-value is larger than the critical value, the null hypothesis can be rejected that each of the coefficients are
not jointly significant and not significantly different than zero. This leads us to the conclusion that the two
variables are jointly significant at a 5% significance level. This implies that a country’s level of trade and
whether or not it is a developed country both have a similar impact on the log of GDP per capita in this
model. Due to this joint significance, one of these variables can be removed from the model and we chose
to remove trade because the developed variable was more significant in MLR II and accounted for more
factors of GDP per capita than trade. When trade was dropped, the variable developed grew more positive
and remained significant at the 1% level.
To check the joint significance of manufacturing and savings, we performed a similar F-test to
test the joint significance between the two explanatory variables. We again created a restricted model,
excluding savings and manufacturing, and an unrestricted model that included all variables, namely our
MLR II. As done previously, we used the R-squared F-test to test the following hypothesis:
H0: β3 =
β5 =
0
H1: H0 is not true
The R-squared values of our restricted and unrestricted models were 0.4732 and 0.5615, respectively. To
calculate the F-value, the following calculation was performed:
2
F = [(R2 ur
/ [(1−R2 ur
)/(n−k−1)]
– R r )/q]
F=
[(0.5616-0.4732)/2] / [(1-0.5616)/118)] = (0.044)/(0.0037) = 11.946
This F-value, similar to above, was also significantly larger than the critical value at 5%, with numerator
degrees of freedom equal to 2 and denominator degrees of freedom equal to 118. The critical value, which
Relationship between Trade and Economic Growth
Group 9
again was 3.07, is much less than the F-value of 11.946, implying that the null hypothesis can be rejected
and that the two variables are jointly significant. This joint significance means that one of the variables
can be dropped from the model. The variable dropped was manufacturing because our thought process led
us to believe that savings would be better at explaining changes in GDP per capita. Savings was also
significant at the 1% level in MLR II whereas manufacturing was insignificant at all levels. Removing
manufacturing increased the coefficient of savings and kept savings significant at the 1% level.
VI.
Conclusions
The findings overall led to a rejection of our original hypothesis, that trade would have a strong
positive correlation with the log of GDP per capita, which was representative of economic growth. In
accounting for outside factors that impact economic growth, we found that while trade does impact
growth, ultimately it may serve more as an indicator of already globalized nations. We reached this
conclusion when the joint significance of trade and developed was tested based on the high
multicollinearity. The constant of the repeated multiple linear regression models was the high significance
of savings on economic growth. If anything, the final model proved that the more funds are put into
developing a domestic economy, the greater the economic growth. From the final regression, we
determined that savings and the developed variable were statistically significant at the 1% level while
unemployment was statistically significant at the 5% level. This is supported by general macroeconomic
theory. Savings, measured as disposable income as a percent of GDP, shows how changes in GDP per
capita directly respond to the demand in the domestic economy. While investment, measured as FDI
inflows, was not a significant number, we found it to be a crucial indicator of the openness of the
domestic economy to global markets and the international community.
Economic growth can be impacted by a wide variety of factors and this model only encapsulated
the ones we deemed important for the scope of this research paper. To truly determine the scope and
impact of trade and trade liberalization on economic growth, it is important to narrow the scope of the
model. Examining a full economy and economic structure required many variables to be accounted for
and reducing the field perhaps by sector or some other form may allow a more significant and nuanced
relationship between trade and economic growth to be uncovered.
Relationship between Trade and Economic Growth
VII.
Group 9
References
Gnangnon, Sèna Kimm. “Multilateral Trade Liberalization and Economic Growth.” Journal of Economic
Integration, vol. 33, no. 2, 2018, pp. 1261–1301.
Makki, Shiva S., Somwaru, Agapi, 2004. “Impact of Foreign Direct Investment and Trade on Economic
Growth” American Journal of Agricultural Economics, Volume 86, Issue 3, pp. 795-801.
Medina-Smith, Emilio J., “Is the Export-Led Growth Hypothesis Valid for Developing Countries? A Case
Study of Costa Rica.” Policy Issues in International Trade and Commodities Study Series, no. 7, 2001.
Singh, Tarlok. “Does International Trade Cause Economic Growth? A Survey.” The World Economy, vol.
33, iss. 11, 2010, pp. 1517-1564.
World Bank. World Development Indicators. The World Bank Group, 2019.
United Nations. “Country Classifications.” World Economic Situation and Prospects, 2017.
Relationship between Trade and Economic Growth
VIII.
Appendix
Stata Outputs
Multicollinearity:
Simple Linear Regression:
Group 9
Relationship between Trade and Economic Growth
Multiple Linear Regression I:
Multiple Linear Regression II:
Group 9
Relationship between Trade and Economic Growth
Group 9
Multiple Linear Regression III:
Countries Used in Research
Afghanistan, Angola, Albania, Argentina, Armenia, Australia, Austria, Azerbaijan, Belgium, Benin,
Burkina Faso, Bangladesh, Bulgaria, Bahrain, Bosnia and Herzegovina, Belarus, Belize, Bolivia, Brazil,
Brunei Darussalam, Bhutan, Botswana, Switzerland, Chile, China, Cote d’Ivoire, Cameroon, Colombia,
Cabo Verde, Costa Rica, Cyprus, Czech Republic, Germany, Djibouti, Denmark, Dominican Republic,
Algeria, Ecuador, Egypt, Arab Rep., Spain, Estonia, Ethiopia, Finland, France, United Kingdom, Georgia,
Ghana, Guinea, Guinea-Bissau, Greece, Guatemala, Honduras, Croatia, Hungary, Indonesia, India,
Ireland, Israel, Italy, Jamaica, Jordan, Japan, Kazakhstan, Kenya, Kyrgyz Republic, Cambodia, Korea,
Rep., Kuwait, Lebanon, Liberia, Sri Lanka, Lithuania, Luxembourg, Latvia, Morocco, Moldova, Mexico,
Malta, Myanmar, Montenegro, Mongolia, Mozambique, Mauritius, Malawi, Malaysia, Namibia, Niger,
Nigeria, Nicaragua, Netherlands, Norway, Nepal, Oman, Pakistan, Panama, Peru, Philippines, Portugal,
Paraguay, Qatar, Romania, Russian Federation, Rwanda, Saudi Arabia, Senegal, Singapore, Sierra Leone,
El Salvador, Slovak Republic, Slovenia, Sweden, Togo, Thailand, Tajikistan, Timor-Leste, Tunisia,
Turkey, Tanzania, Uganda, Ukraine, Uruguay, United States, Vietnam, South Africa, Zimbabwe
FRED Graph Observations
Federal Reserve Economic Data
Link: https://fred.stlouisfed.org
Help: https://fredhelp.stlouisfed.org
Economic Research Division
Federal Reserve Bank of St. Louis
MORTGAGE30US
30-Year Fixed Rate Mortgage Average in the United States, Percent, Weekly, Not Seasonally Adjuste
Frequency: Weekly, Ending Thursday
observation_date
MORTGAGE30US
1971-04-02
1971-04-09
1971-04-16
1971-04-23
1971-04-30
1971-05-07
1971-05-14
1971-05-21
1971-05-28
1971-06-04
1971-06-11
1971-06-18
1971-06-25
1971-07-02
1971-07-09
1971-07-16
1971-07-23
1971-07-30
1971-08-06
1971-08-13
1971-08-20
1971-08-27
1971-09-03
1971-09-10
1971-09-17
1971-09-24
1971-10-01
1971-10-08
1971-10-15
1971-10-22
1971-10-29
1971-11-05
1971-11-12
1971-11-19
1971-11-26
1971-12-03
1971-12-10
1971-12-17
1971-12-24
1971-12-31
1972-01-07
7,33
7,31
7,31
7,31
7,29
7,38
7,42
7,44
7,46
7,52
7,52
7,54
7,54
7,54
7,54
7,60
7,65
7,69
7,66
7,73
7,71
7,69
7,71
7,67
7,70
7,67
7,67
7,63
7,63
7,58
7,63
7,59
7,56
7,54
7,51
7,49
7,47
7,48
7,48
7,48
7,46
1972-01-14
1972-01-21
1972-01-28
1972-02-04
1972-02-11
1972-02-18
1972-02-25
1972-03-03
1972-03-10
1972-03-17
1972-03-24
1972-03-31
1972-04-07
1972-04-14
1972-04-21
1972-04-28
1972-05-05
1972-05-12
1972-05-19
1972-05-26
1972-06-02
1972-06-09
1972-06-16
1972-06-23
1972-06-30
1972-07-07
1972-07-14
1972-07-21
1972-07-28
1972-08-04
1972-08-11
1972-08-18
1972-08-25
1972-09-01
1972-09-08
1972-09-15
1972-09-22
1972-09-29
1972-10-06
1972-10-13
1972-10-20
1972-10-27
1972-11-03
1972-11-10
1972-11-17
1972-11-24
1972-12-01
1972-12-08
1972-12-15
1972-12-22
1972-12-29
1973-01-05
7,46
7,43
7,40
7,35
7,33
7,31
7,31
7,32
7,32
7,31
7,31
7,23
7,25
7,29
7,29
7,33
7,33
7,38
7,38
7,40
7,36
7,38
7,38
7,36
7,38
7,38
7,40
7,40
7,40
7,35
7,41
7,42
7,42
7,42
7,42
7,42
7,41
7,43
7,41
7,41
7,44
7,42
7,43
7,42
7,42
7,44
7,45
7,43
7,43
7,45
7,45
7,44
1973-01-12
1973-01-19
1973-01-26
1973-02-02
1973-02-09
1973-02-16
1973-02-23
1973-03-02
1973-03-09
1973-03-16
1973-03-23
1973-03-30
1973-04-06
1973-04-13
1973-04-20
1973-04-27
1973-05-04
1973-05-11
1973-05-18
1973-05-24
1973-06-01
1973-06-08
1973-06-15
1973-06-22
1973-06-29
1973-07-06
1973-07-13
1973-07-20
1973-07-27
1973-08-03
1973-08-10
1973-08-17
1973-08-24
1973-08-31
1973-09-07
1973-09-14
1973-09-21
1973-09-28
1973-10-05
1973-10-12
1973-10-19
1973-10-26
1973-11-02
1973-11-09
1973-11-16
1973-11-23
1973-11-30
1973-12-07
1973-12-14
1973-12-21
1973-12-28
1974-01-04
7,44
7,44
7,43
7,43
7,43
7,45
7,45
7,45
7,45
7,45
7,45
7,49
7,51
7,54
7,56
7,56
7,58
7,64
7,69
7,70
7,70
7,73
7,73
7,75
7,76
7,89
8,01
8,12
8,18
8,26
8,40
8,55
8,61
8,66
8,77
8,81
8,83
8,85
8,82
8,83
8,75
8,68
8,62
8,59
8,58
8,57
8,55
8,53
8,53
8,53
8,56
8,56
1974-01-11
1974-01-18
1974-01-25
1974-02-01
1974-02-08
1974-02-15
1974-02-22
1974-03-01
1974-03-08
1974-03-15
1974-03-22
1974-03-29
1974-04-05
1974-04-12
1974-04-19
1974-04-26
1974-05-03
1974-05-10
1974-05-17
1974-05-24
1974-05-31
1974-06-07
1974-06-14
1974-06-21
1974-06-28
1974-07-05
1974-07-12
1974-07-19
1974-07-26
1974-08-02
1974-08-09
1974-08-16
1974-08-23
1974-08-30
1974-09-06
1974-09-13
1974-09-20
1974-09-27
1974-10-04
1974-10-11
1974-10-18
1974-10-25
1974-11-01
1974-11-08
1974-11-15
1974-11-22
1974-11-29
1974-12-06
1974-12-13
1974-12-20
1974-12-27
1975-01-03
8,53
8,55
8,52
8,48
8,46
8,46
8,42
8,41
8,41
8,40
8,40
8,41
8,44
8,53
8,63
8,73
8,87
8,98
8,97
9,01
9,03
9,06
9,11
9,07
9,10
9,14
9,19
9,37
9,42
9,47
9,50
9,60
9,62
9,74
9,88
9,92
10,00
10,03
10,02
9,96
9,99
9,94
9,87
9,81
9,81
9,73
9,72
9,69
9,63
9,58
9,56
9,60
1975-01-10
1975-01-17
1975-01-24
1975-01-31
1975-02-07
1975-02-14
1975-02-21
1975-02-28
1975-03-07
1975-03-14
1975-03-21
1975-03-28
1975-04-04
1975-04-11
1975-04-18
1975-04-25
1975-05-02
1975-05-09
1975-05-16
1975-05-23
1975-05-30
1975-06-06
1975-06-13
1975-06-20
1975-06-27
1975-07-03
1975-07-11
1975-07-18
1975-07-25
1975-08-01
1975-08-08
1975-08-15
1975-08-22
1975-08-29
1975-09-05
1975-09-12
1975-09-19
1975-09-26
1975-10-03
1975-10-10
1975-10-17
1975-10-24
1975-10-31
1975-11-07
1975-11-14
1975-11-21
1975-11-28
1975-12-05
1975-12-12
1975-12-19
1975-12-26
1976-01-02
9,49
9,43
9,35
9,29
9,20
9,13
9,07
9,02
9,00
8,89
8,86
8,86
8,83
8,81
8,80
8,84
8,92
8,88
8,92
8,92
8,89
8,89
8,90
8,88
8,90
8,88
8,90
8,89
8,89
8,89
8,89
8,93
8,98
9,02
9,08
9,16
9,14
9,14
9,20
9,21
9,21
9,26
9,24
9,19
9,16
9,12
9,11
9,11
9,11
9,08
9,09
9,10
1976-01-09
1976-01-16
1976-01-23
1976-01-30
1976-02-06
1976-02-13
1976-02-20
1976-02-27
1976-03-05
1976-03-12
1976-03-19
1976-03-26
1976-04-02
1976-04-09
1976-04-16
1976-04-23
1976-04-30
1976-05-07
1976-05-14
1976-05-21
1976-05-28
1976-06-04
1976-06-11
1976-06-18
1976-06-25
1976-07-02
1976-07-09
1976-07-16
1976-07-23
1976-07-30
1976-08-06
1976-08-13
1976-08-20
1976-08-27
1976-09-03
1976-09-10
1976-09-17
1976-09-24
1976-10-01
1976-10-08
1976-10-15
1976-10-22
1976-10-29
1976-11-05
1976-11-12
1976-11-19
1976-11-26
1976-12-03
1976-12-10
1976-12-17
1976-12-24
1976-12-31
9,07
9,01
9,00
8,90
8,86
8,83
8,81
8,75
8,77
8,75
8,75
8,75
8,70
8,70
8,75
8,75
8,75
8,75
8,75
8,78
8,78
8,78
8,83
8,88
8,90
8,93
8,93
8,93
8,90
8,98
9,00
9,00
9,00
9,00
9,00
8,97
8,97
8,97
8,90
8,95
8,95
8,95
8,90
8,85
8,80
8,80
8,80
8,80
8,80
8,80
8,78
8,78
1977-01-07
1977-01-14
1977-01-21
1977-01-28
1977-02-04
1977-02-11
1977-02-18
1977-02-25
1977-03-04
1977-03-11
1977-03-18
1977-03-25
1977-04-01
1977-04-08
1977-04-15
1977-04-22
1977-04-29
1977-05-06
1977-05-13
1977-05-20
1977-05-27
1977-06-03
1977-06-10
1977-06-17
1977-06-24
1977-07-01
1977-07-08
1977-07-15
1977-07-22
1977-07-29
1977-08-05
1977-08-12
1977-08-19
1977-08-26
1977-09-02
1977-09-09
1977-09-16
1977-09-23
1977-09-30
1977-10-07
1977-10-14
1977-10-21
1977-10-28
1977-11-04
1977-11-11
1977-11-18
1977-11-25
1977-12-02
1977-12-09
1977-12-16
1977-12-23
1977-12-30
8,70
8,73
8,73
8,73
8,68
8,70
8,65
8,65
8,65
8,70
8,70
8,70
8,70
8,75
8,75
8,78
8,78
8,78
8,83
8,85
8,85
8,85
8,85
8,85
8,88
8,95
8,93
8,95
8,95
8,93
8,95
8,95
8,93
8,93
8,88
8,90
8,90
8,90
8,90
8,93
8,93
8,93
8,90
8,90
8,93
8,93
8,93
8,95
8,95
8,95
8,95
9,00
1978-01-06
1978-01-13
1978-01-20
1978-01-27
1978-02-03
1978-02-10
1978-02-17
1978-02-24
1978-03-03
1978-03-10
1978-03-17
1978-03-24
1978-03-31
1978-04-07
1978-04-14
1978-04-21
1978-04-28
1978-05-05
1978-05-12
1978-05-19
1978-05-26
1978-06-02
1978-06-09
1978-06-16
1978-06-23
1978-06-30
1978-07-07
1978-07-14
1978-07-21
1978-07-28
1978-08-04
1978-08-11
1978-08-18
1978-08-25
1978-09-01
1978-09-08
1978-09-15
1978-09-22
1978-09-29
1978-10-06
1978-10-13
1978-10-20
1978-10-27
1978-11-03
1978-11-10
1978-11-17
1978-11-24
1978-12-01
1978-12-08
1978-12-15
1978-12-22
1978-12-29
9,00
9,03
8,98
9,05
9,13
9,15
9,15
9,15
9,15
9,15
9,23
9,23
9,25
9,28
9,33
9,38
9,43
9,48
9,55
9,58
9,68
9,68
9,70
9,73
9,70
9,73
9,73
9,73
9,75
9,75
9,78
9,78
9,78
9,80
9,75
9,75
9,75
9,75
9,78
9,85
9,85
9,85
9,88
9,90
10,05
10,20
10,28
10,30
10,35
10,35
10,35
10,38
1979-01-05
1979-01-12
1979-01-19
1979-01-26
1979-02-02
1979-02-09
1979-02-16
1979-02-23
1979-03-02
1979-03-09
1979-03-16
1979-03-23
1979-03-30
1979-04-06
1979-04-13
1979-04-20
1979-04-27
1979-05-04
1979-05-11
1979-05-18
1979-05-25
1979-06-01
1979-06-08
1979-06-15
1979-06-22
1979-06-29
1979-07-06
1979-07-13
1979-07-20
1979-07-27
1979-08-03
1979-08-10
1979-08-17
1979-08-24
1979-08-31
1979-09-07
1979-09-14
1979-09-21
1979-09-28
1979-10-05
1979-10-12
1979-10-19
1979-10-26
1979-11-02
1979-11-09
1979-11-16
1979-11-23
1979-11-30
1979-12-07
1979-12-14
1979-12-21
1979-12-28
10,38
10,38
10,40
10,40
10,40
10,43
10,40
10,40
10,43
10,40
10,40
10,45
10,45
10,48
10,48
10,50
10,53
10,60
10,68
10,73
10,75
10,90
11,03
11,05
11,10
11,10
11,13
11,08
11,08
11,08
11,08
11,08
11,08
11,10
11,13
11,20
11,30
11,35
11,35
11,35
11,45
11,75
12,00
12,80
12,85
12,80
12,80
12,90
12,90
12,90
12,90
12,90
1980-01-04
1980-01-11
1980-01-18
1980-01-25
1980-02-01
1980-02-08
1980-02-15
1980-02-22
1980-02-29
1980-03-07
1980-03-14
1980-03-21
1980-03-28
1980-04-04
1980-04-11
1980-04-18
1980-04-25
1980-05-02
1980-05-09
1980-05-16
1980-05-23
1980-05-30
1980-06-06
1980-06-13
1980-06-20
1980-06-27
1980-07-04
1980-07-11
1980-07-18
1980-07-25
1980-08-01
1980-08-08
1980-08-15
1980-08-22
1980-08-29
1980-09-05
1980-09-12
1980-09-19
1980-09-26
1980-10-03
1980-10-10
1980-10-17
1980-10-24
1980-10-31
1980-11-07
1980-11-14
1980-11-21
1980-11-28
1980-12-05
1980-12-12
1980-12-19
1980-12-26
12,85
12,90
12,87
12,89
12,85
12,85
12,88
13,03
13,59
14,00
15,40
15,70
16,03
16,35
16,35
16,35
16,25
15,90
14,68
14,15
13,38
13,20
13,06
12,85
12,58
12,35
12,18
12,23
12,18
12,18
12,25
12,25
12,55
12,80
12,95
13,03
13,08
13,25
13,43
13,60
13,73
13,78
13,85
14,00
14,08
14,18
14,28
14,28
14,43
14,83
14,95
14,95
1981-01-02
1981-01-09
1981-01-16
1981-01-23
1981-01-30
1981-02-06
1981-02-13
1981-02-20
1981-02-27
1981-03-06
1981-03-13
1981-03-20
1981-03-27
1981-04-03
1981-04-10
1981-04-17
1981-04-24
1981-05-01
1981-05-08
1981-05-15
1981-05-22
1981-05-29
1981-06-05
1981-06-12
1981-06-19
1981-06-26
1981-07-03
1981-07-10
1981-07-17
1981-07-24
1981-07-31
1981-08-07
1981-08-14
1981-08-21
1981-08-28
1981-09-04
1981-09-11
1981-09-18
1981-09-25
1981-10-02
1981-10-09
1981-10-16
1981-10-21
1981-10-30
1981-11-06
1981-11-13
1981-11-20
1981-11-27
1981-12-04
1981-12-11
1981-12-18
1981-12-25
14,95
14,80
14,85
14,85
15,07
15,00
15,03
15,20
15,30
15,40
15,40
15,40
15,40
15,40
15,50
15,65
15,77
15,82
16,12
16,64
16,63
16,80
16,76
16,69
16,71
16,62
16,64
16,79
16,74
16,88
17,11
17,13
17,27
17,26
17,48
17,79
18,22
18,27
18,36
18,28
18,63
18,53
18,39
18,44
18,37
18,02
17,70
17,21
16,90
16,94
16,90
16,95
1981-12-31
1982-01-08
1982-01-15
1982-01-22
1982-01-29
1982-02-05
1982-02-12
1982-02-19
1982-02-26
1982-03-05
1982-03-12
1982-03-19
1982-03-26
1982-04-02
1982-04-09
1982-04-16
1982-04-23
1982-04-30
1982-05-07
1982-05-14
1982-05-21
1982-05-28
1982-06-04
1982-06-11
1982-06-18
1982-06-25
1982-07-02
1982-07-09
1982-07-16
1982-07-23
1982-07-30
1982-08-06
1982-08-13
1982-08-20
1982-08-27
1982-09-03
1982-09-10
1982-09-17
1982-09-24
1982-10-01
1982-10-08
1982-10-15
1982-10-22
1982-10-29
1982-11-05
1982-11-12
1982-11-19
1982-11-26
1982-12-03
1982-12-10
1982-12-17
1982-12-24
17,04
17,30
17,44
17,61
17,59
17,56
17,65
17,66
17,52
17,29
17,19
17,12
17,04
16,95
16,91
16,93
16,86
16,81
16,78
16,63
16,67
16,63
16,65
16,70
16,71
16,73
16,87
16,93
16,88
16,75
16,65
16,55
16,44
16,21
15,88
15,59
15,56
15,38
15,19
15,13
14,96
14,60
14,20
14,15
13,91
13,84
13,78
13,77
13,66
13,66
13,63
13,60
1982-12-31
1983-01-07
1983-01-14
1983-01-21
1983-01-28
1983-02-04
1983-02-11
1983-02-18
1983-02-25
1983-03-04
1983-03-11
1983-03-18
1983-03-25
1983-04-01
1983-04-08
1983-04-15
1983-04-22
1983-04-29
1983-05-06
1983-05-13
1983-05-20
1983-05-27
1983-06-03
1983-06-10
1983-06-17
1983-06-24
1983-07-01
1983-07-08
1983-07-15
1983-07-22
1983-07-29
1983-08-05
1983-08-12
1983-08-19
1983-08-26
1983-09-02
1983-09-09
1983-09-16
1983-09-23
1983-09-30
1983-10-07
1983-10-14
1983-10-21
1983-10-28
1983-11-04
1983-11-11
1983-11-18
1983-11-25
1983-12-02
1983-12-09
1983-12-16
1983-12-23
13,57
13,46
13,31
13,12
13,10
13,06
13,06
13,07
12,98
12,74
12,79
12,81
12,86
12,82
12,82
12,79
12,75
12,73
12,71
12,59
12,55
12,68
12,74
12,82
12,96
12,96
13,08
13,30
13,50
13,58
13,65
13,73
13,84
13,89
13,78
13,77
13,77
13,72
13,72
13,65
13,59
13,60
13,52
13,43
13,42
13,47
13,42
13,43
13,41
13,38
13,42
13,46
1983-12-30
1984-01-06
1984-01-13
1984-01-20
1984-01-27
1984-02-03
1984-02-10
1984-02-17
1984-02-24
1984-03-02
1984-03-09
1984-03-16
1984-03-23
1984-03-30
1984-04-06
1984-04-13
1984-04-20
1984-04-27
1984-05-04
1984-05-11
1984-05-18
1984-05-25
1984-06-01
1984-06-08
1984-06-15
1984-06-22
1984-06-29
1984-07-06
1984-07-13
1984-07-20
1984-07-27
1984-08-03
1984-08-10
1984-08-17
1984-08-24
1984-08-31
1984-09-07
1984-09-14
1984-09-21
1984-09-28
1984-10-05
1984-10-12
1984-10-19
1984-10-26
1984-11-02
1984-11-09
1984-11-16
1984-11-23
1984-11-30
1984-12-07
1984-12-14
1984-12-21
13,43
13,43
13,40
13,35
13,29
13,26
13,23
13,19
13,25
13,23
13,30
13,37
13,48
13,55
13,63
13,58
13,67
13,73
13,78
13,87
14,04
14,08
14,29
14,33
14,47
14,49
14,50
14,66
14,68
14,66
14,67
14,68
14,54
14,39
14,36
14,38
14,42
14,43
14,29
14,26
14,18
14,19
14,10
14,05
13,85
13,74
13,63
13,55
13,42
13,20
13,20
13,18
1984-12-28
1985-01-04
1985-01-11
1985-01-18
1985-01-25
1985-02-01
1985-02-08
1985-02-15
1985-02-22
1985-03-01
1985-03-08
1985-03-15
1985-03-22
1985-03-29
1985-04-05
1985-04-12
1985-04-19
1985-04-26
1985-05-03
1985-05-10
1985-05-17
1985-05-24
1985-05-31
1985-06-07
1985-06-14
1985-06-21
1985-06-28
1985-07-05
1985-07-12
1985-07-19
1985-07-26
1985-08-02
1985-08-09
1985-08-16
1985-08-23
1985-08-30
1985-09-06
1985-09-13
1985-09-20
1985-09-27
1985-10-04
1985-10-11
1985-10-18
1985-10-25
1985-11-01
1985-11-08
1985-11-15
1985-11-22
1985-11-29
1985-12-06
1985-12-13
1985-12-20
13,14
13,10
13,12
13,12
12,96
12,93
12,91
12,90
12,94
13,02
13,10
13,20
13,24
13,29
13,27
13,23
13,16
13,12
13,07
13,02
12,94
12,83
12,71
12,39
12,27
12,05
12,15
12,13
12,03
11,94
12,03
12,17
12,23
12,24
12,18
12,11
12,15
12,24
12,21
12,17
12,17
12,17
12,13
12,07
12,01
11,90
11,79
11,64
11,58
11,50
11,31
11,14
1985-12-27
1986-01-03
1986-01-10
1986-01-17
1986-01-24
1986-01-31
1986-02-07
1986-02-14
1986-02-21
1986-02-28
1986-03-07
1986-03-14
1986-03-21
1986-03-28
1986-04-04
1986-04-11
1986-04-18
1986-04-25
1986-05-02
1986-05-09
1986-05-16
1986-05-23
1986-05-30
1986-06-06
1986-06-13
1986-06-20
1986-06-27
1986-07-04
1986-07-11
1986-07-18
1986-07-25
1986-08-01
1986-08-08
1986-08-15
1986-08-22
1986-08-29
1986-09-05
1986-09-12
1986-09-19
1986-09-26
1986-10-03
1986-10-10
1986-10-17
1986-10-24
1986-10-31
1986-11-07
1986-11-14
1986-11-21
1986-11-28
1986-12-05
1986-12-12
1986-12-19
11,09
10,81
10,77
10,99
10,97
10,89
10,85
10,80
10,68
10,51
10,20
10,01
10,01
10,10
9,99
9,98
9,92
9,86
9,90
10,00
10,08
10,36
10,38
10,74
10,76
10,61
10,62
10,61
10,59
10,43
10,40
10,40
10,40
10,23
10,04
9,93
9,90
9,96
10,07
10,10
10,08
9,99
9,96
9,95
9,89
9,83
9,81
9,64
9,50
9,30
9,35
9,30
1986-12-26
1987-01-02
1987-01-09
1987-01-16
1987-01-23
1987-01-30
1987-02-06
1987-02-13
1987-02-20
1987-02-27
1987-03-06
1987-03-13
1987-03-20
1987-03-27
1987-04-03
1987-04-10
1987-04-17
1987-04-24
1987-05-01
1987-05-08
1987-05-15
1987-05-22
1987-05-29
1987-06-05
1987-06-12
1987-06-19
1987-06-26
1987-07-03
1987-07-10
1987-07-17
1987-07-24
1987-07-31
1987-08-07
1987-08-14
1987-08-21
1987-08-28
1987-09-04
1987-09-11
1987-09-18
1987-09-25
1987-10-02
1987-10-09
1987-10-16
1987-10-23
1987-10-30
1987-11-06
1987-11-13
1987-11-20
1987-11-27
1987-12-04
1987-12-11
1987-12-18
9,29
9,37
9,32
9,21
9,04
9,08
9,06
9,09
9,11
9,07
9,03
9,05
9,03
9,03
9,26
9,43
10,27
10,37
10,47
10,52
10,48
10,81
10,70
10,70
10,66
10,44
10,35
10,36
10,30
10,23
10,23
10,27
10,35
10,34
10,30
10,33
10,63
10,91
10,99
11,02
11,18
11,21
11,58
11,36
10,97
10,79
10,66
10,60
10,55
10,60
10,66
10,69
1987-12-25
1987-12-31
1988-01-08
1988-01-15
1988-01-22
1988-01-29
1988-02-05
1988-02-12
1988-02-19
1988-02-26
1988-03-04
1988-03-11
1988-03-18
1988-03-25
1988-04-01
1988-04-08
1988-04-15
1988-04-22
1988-04-29
1988-05-06
1988-05-13
1988-05-20
1988-05-27
1988-06-03
1988-06-10
1988-06-17
1988-06-24
1988-07-01
1988-07-08
1988-07-15
1988-07-22
1988-07-29
1988-08-05
1988-08-12
1988-08-19
1988-08-26
1988-09-02
1988-09-09
1988-09-16
1988-09-23
1988-09-30
1988-10-07
1988-10-14
1988-10-21
1988-10-28
1988-11-04
1988-11-11
1988-11-18
1988-11-25
1988-12-02
1988-12-09
1988-12-16
10,64
10,61
10,50
10,53
10,34
10,16
9,94
9,84
9,92
9,87
9,85
9,96
9,92
9,99
10,05
10,19
10,19
10,30
10,28
10,32
10,40
10,52
10,58
10,58
10,51
10,35
10,40
10,39
10,38
10,44
10,46
10,49
10,44
10,57
10,71
10,67
10,65
10,53
10,40
10,40
10,42
10,38
10,33
10,28
10,22
10,12
10,24
10,31
10,39
10,44
10,46
10,71
1988-12-23
1988-12-30
1989-01-06
1989-01-13
1989-01-20
1989-01-27
1989-02-03
1989-02-10
1989-02-17
1989-02-24
1989-03-03
1989-03-10
1989-03-17
1989-03-24
1989-03-31
1989-04-07
1989-04-14
1989-04-21
1989-04-28
1989-05-05
1989-05-12
1989-05-19
1989-05-26
1989-06-02
1989-06-09
1989-06-16
1989-06-23
1989-06-30
1989-07-07
1989-07-14
1989-07-21
1989-07-28
1989-08-04
1989-08-11
1989-08-18
1989-08-25
1989-09-01
1989-09-08
1989-09-15
1989-09-22
1989-09-29
1989-10-06
1989-10-13
1989-10-20
1989-10-27
1989-11-03
1989-11-10
1989-11-17
1989-11-24
1989-12-01
1989-12-08
1989-12-15
10,68
10,77
10,80
10,81
10,71
10,60
10,55
10,56
10,69
10,78
10,91
10,86
10,98
11,22
11,19
11,07
11,11
10,99
11,03
10,97
10,93
10,69
10,50
10,48
10,20
10,04
10,19
10,07
10,03
9,82
9,87
9,81
9,68
9,96
10,09
10,21
10,22
10,17
10,05
10,03
10,16
10,10
9,95
9,92
9,82
9,82
9,79
9,72
9,74
9,74
9,76
9,75
1989-12-22
1989-12-29
1990-01-05
1990-01-12
1990-01-19
1990-01-26
1990-02-02
1990-02-09
1990-02-16
1990-02-23
1990-03-02
1990-03-09
1990-03-16
1990-03-23
1990-03-30
1990-04-06
1990-04-13
1990-04-20
1990-04-27
1990-05-04
1990-05-11
1990-05-18
1990-05-25
1990-06-01
1990-06-08
1990-06-15
1990-06-22
1990-06-29
1990-07-06
1990-07-13
1990-07-20
1990-07-27
1990-08-03
1990-08-10
1990-08-17
1990-08-24
1990-08-31
1990-09-07
1990-09-14
1990-09-21
1990-09-28
1990-10-05
1990-10-12
1990-10-19
1990-10-26
1990-11-02
1990-11-09
1990-11-16
1990-11-23
1990-11-30
1990-12-07
1990-12-14
9,69
9,78
9,83
9,80
9,90
10,05
10,17
10,21
10,10
10,31
10,23
10,29
10,34
10,26
10,22
10,26
10,25
10,41
10,56
10,67
10,54
10,37
10,33
10,29
10,10
10,12
10,16
10,15
10,06
10,11
9,99
9,98
9,84
10,08
10,05
10,29
10,24
10,19
10,13
10,16
10,22
10,08
10,22
10,24
10,17
10,13
10,09
10,02
9,93
9,90
9,81
9,56
1990-12-21
1990-12-28
1991-01-04
1991-01-11
1991-01-18
1991-01-25
1991-02-01
1991-02-08
1991-02-15
1991-02-22
1991-03-01
1991-03-08
1991-03-15
1991-03-22
1991-03-29
1991-04-05
1991-04-12
1991-04-19
1991-04-26
1991-05-03
1991-05-10
1991-05-17
1991-05-24
1991-05-31
1991-06-07
1991-06-14
1991-06-21
1991-06-28
1991-07-05
1991-07-12
1991-07-19
1991-07-26
1991-08-02
1991-08-09
1991-08-16
1991-08-23
1991-08-30
1991-09-06
1991-09-13
1991-09-20
1991-09-27
1991-10-04
1991-10-11
1991-10-18
1991-10-25
1991-11-01
1991-11-08
1991-11-15
1991-11-22
1991-11-29
1991-12-06
1991-12-13
9,64
9,68
9,56
9,63
9,75
9,61
9,56
9,36
9,25
9,29
9,40
9,49
9,50
9,59
9,52
9,49
9,48
9,47
9,53
9,47
9,47
9,50
9,47
9,45
9,48
9,66
9,65
9,67
9,62
9,64
9,54
9,50
9,44
9,27
9,19
9,17
9,15
9,14
9,02
8,95
8,92
8,87
8,82
8,82
8,91
8,78
8,76
8,69
8,63
8,70
8,62
8,53
1991-12-20
1991-12-27
1992-01-03
1992-01-10
1992-01-17
1992-01-24
1992-01-31
1992-02-07
1992-02-14
1992-02-21
1992-02-28
1992-03-06
1992-03-13
1992-03-20
1992-03-27
1992-04-03
1992-04-10
1992-04-17
1992-04-24
1992-05-01
1992-05-08
1992-05-15
1992-05-22
1992-05-29
1992-06-05
1992-06-12
1992-06-19
1992-06-26
1992-07-03
1992-07-10
1992-07-17
1992-07-24
1992-07-31
1992-08-07
1992-08-14
1992-08-21
1992-08-28
1992-09-04
1992-09-11
1992-09-18
1992-09-24
1992-10-02
1992-10-09
1992-10-16
1992-10-23
1992-10-30
1992-11-06
1992-11-13
1992-11-20
1992-11-27
1992-12-04
1992-12-11
8,49
8,35
8,24
8,23
8,45
8,56
8,68
8,67
8,73
8,82
8,83
8,85
8,88
9,03
8,98
8,96
8,84
8,76
8,85
8,84
8,75
8,64
8,53
8,60
8,59
8,54
8,48
8,43
8,29
8,13
8,09
8,08
8,05
8,06
7,96
7,87
8,01
7,94
7,84
7,89
8,02
7,93
8,01
8,06
8,23
8,21
8,29
8,32
8,32
8,29
8,34
8,23
1992-12-18
1992-12-25
1992-12-31
1993-01-08
1993-01-15
1993-01-22
1993-01-29
1993-02-05
1993-02-12
1993-02-19
1993-02-26
1993-03-05
1993-03-12
1993-03-19
1993-03-26
1993-04-02
1993-04-09
1993-04-16
1993-04-23
1993-04-30
1993-05-07
1993-05-14
1993-05-21
1993-05-28
1993-06-04
1993-06-11
1993-06-18
1993-06-25
1993-07-02
1993-07-09
1993-07-16
1993-07-23
1993-07-30
1993-08-06
1993-08-13
1993-08-20
1993-08-27
1993-09-03
1993-09-10
1993-09-17
1993-09-24
1993-10-01
1993-10-08
1993-10-15
1993-10-22
1993-10-29
1993-11-05
1993-11-12
1993-11-19
1993-11-26
1993-12-04
1993-12-10
8,19
8,13
8,14
8,07
8,04
8,00
7,86
7,80
7,75
7,65
7,53
7,44
7,47
7,57
7,50
7,53
7,57
7,45
7,38
7,43
7,42
7,42
7,52
7,50
7,47
7,48
7,38
7,34
7,23
7,19
7,16
7,20
7,25
7,21
7,17
7,10
6,97
6,93
6,82
6,96
6,95
6,89
6,87
6,81
6,74
6,86
7,11
7,12
7,08
7,31
7,25
7,14
1993-12-17
1993-12-24
1993-12-31
1994-01-07
1994-01-14
1994-01-21
1994-01-28
1994-02-04
1994-02-11
1994-02-18
1994-02-25
1994-03-04
1994-03-11
1994-03-18
1994-03-25
1994-04-01
1994-04-08
1994-04-15
1994-04-22
1994-04-29
1994-05-06
1994-05-13
1994-05-20
1994-05-27
1994-06-03
1994-06-10
1994-06-17
1994-06-24
1994-07-01
1994-07-08
1994-07-15
1994-07-22
1994-07-29
1994-08-05
1994-08-12
1994-08-19
1994-08-26
1994-09-02
1994-09-09
1994-09-16
1994-09-23
1994-09-30
1994-10-07
1994-10-14
1994-10-21
1994-10-28
1994-11-04
1994-11-11
1994-11-18
1994-11-25
1994-12-02
1994-12-09
7,17
7,17
7,13
7,23
6,99
7,05
6,97
6,97
7,21
7,11
7,32
7,51
7,63
7,76
7,80
8,04
8,47
8,26
8,49
8,32
8,53
8,77
8,56
8,53
8,55
8,25
8,33
8,46
8,57
8,68
8,72
8,53
8,57
8,38
8,57
8,54
8,56
8,48
8,51
8,66
8,73
8,82
8,89
8,93
8,85
9,03
9,05
9,19
9,19
9,25
9,23
9,15
1994-12-16
1994-12-23
1994-12-30
1995-01-06
1995-01-13
1995-01-20
1995-01-27
1995-02-03
1995-02-10
1995-02-17
1995-02-24
1995-03-03
1995-03-10
1995-03-17
1995-03-24
1995-03-31
1995-04-07
1995-04-14
1995-04-21
1995-04-28
1995-05-05
1995-05-12
1995-05-19
1995-05-26
1995-06-02
1995-06-09
1995-06-16
1995-06-23
1995-06-30
1995-07-07
1995-07-14
1995-07-21
1995-07-28
1995-08-04
1995-08-11
1995-08-18
1995-08-25
1995-09-01
1995-09-08
1995-09-15
1995-09-22
1995-09-29
1995-10-06
1995-10-13
1995-10-20
1995-10-27
1995-11-03
1995-11-09
1995-11-17
1995-11-24
1995-12-01
1995-12-08
9,25
9,18
9,18
9,22
9,19
9,05
9,13
8,94
8,80
8,84
8,73
8,53
8,62
8,38
8,40
8,38
8,41
8,37
8,24
8,26
8,27
7,87
7,83
7,85
7,71
7,51
7,55
7,53
7,53
7,63
7,41
7,60
7,79
7,82
7,80
7,94
7,88
7,76
7,63
7,60
7,57
7,62
7,57
7,50
7,38
7,45
7,44
7,37
7,35
7,35
7,33
7,18
1995-12-15
1995-12-22
1995-12-29
1996-01-05
1996-01-12
1996-01-19
1996-01-26
1996-02-02
1996-02-09
1996-02-16
1996-02-23
1996-03-01
1996-03-08
1996-03-15
1996-03-22
1996-03-29
1996-04-05
1996-04-12
1996-04-19
1996-04-26
1996-05-03
1996-05-10
1996-05-17
1996-05-24
1996-05-31
1996-06-07
1996-06-14
1996-06-21
1996-06-28
1996-07-05
1996-07-12
1996-07-19
1996-07-26
1996-08-02
1996-08-09
1996-08-16
1996-08-23
1996-08-30
1996-09-06
1996-09-13
1996-09-20
1996-09-27
1996-10-04
1996-10-11
1996-10-18
1996-10-25
1996-11-01
1996-11-08
1996-11-15
1996-11-22
1996-11-29
1996-12-06
7,15
7,23
7,11
7,02
7,08
7,02
7,00
7,02
7,02
6,94
7,32
7,41
7,38
7,83
7,81
7,69
7,78
8,05
7,95
7,92
7,99
8,24
8,08
8,01
8,03
8,30
8,39
8,30
8,29
8,14
8,42
8,23
8,19
8,23
7,88
7,88
7,93
8,09
8,34
8,28
8,14
8,16
8,06
7,86
7,88
7,86
7,78
7,67
7,59
7,53
7,52
7,44
1996-12-13
1996-12-20
1996-12-27
1997-01-03
1997-01-10
1997-01-17
1997-01-24
1997-01-31
1997-02-07
1997-02-14
1997-02-21
1997-02-28
1997-03-07
1997-03-14
1997-03-21
1997-03-28
1997-04-04
1997-04-11
1997-04-18
1997-04-25
1997-05-02
1997-05-09
1997-05-16
1997-05-23
1997-05-30
1997-06-06
1997-06-13
1997-06-20
1997-06-27
1997-07-04
1997-07-11
1997-07-18
1997-07-25
1997-08-01
1997-08-08
1997-08-15
1997-08-22
1997-08-29
1997-09-05
1997-09-12
1997-09-19
1997-09-26
1997-10-03
1997-10-10
1997-10-17
1997-10-24
1997-10-31
1997-11-07
1997-11-14
1997-11-21
1997-11-28
1997-12-05
7,57
7,74
7,64
7,67
7,85
7,87
7,85
7,88
7,74
7,65
7,56
7,65
7,84
7,84
7,94
7,97
8,18
8,15
8,16
8,08
8,01
7,94
7,91
7,92
7,94
7,85
7,72
7,61
7,58
7,62
7,47
7,47
7,43
7,36
7,46
7,54
7,46
7,58
7,53
7,53
7,38
7,28
7,31
7,26
7,34
7,35
7,21
7,24
7,23
7,18
7,17
7,15
1997-12-12
1997-12-19
1997-12-26
1998-01-02
1998-01-09
1998-01-16
1998-01-23
1998-01-30
1998-02-06
1998-02-13
1998-02-20
1998-02-28
1998-03-06
1998-03-13
1998-03-20
1998-03-27
1998-04-03
1998-04-10
1998-04-17
1998-04-24
1998-05-01
1998-05-08
1998-05-15
1998-05-22
1998-05-29
1998-06-05
1998-06-12
1998-06-19
1998-06-26
1998-07-03
1998-07-10
1998-07-17
1998-07-24
1998-07-31
1998-08-07
1998-08-14
1998-08-21
1998-08-28
1998-09-04
1998-09-11
1998-09-18
1998-09-25
1998-10-02
1998-10-09
1998-10-16
1998-10-23
1998-10-30
1998-11-06
1998-11-13
1998-11-20
1998-11-27
1998-12-04
7,17
7,07
6,99
7,03
6,94
6,89
6,99
7,12
7,03
7,06
6,99
7,09
7,19
7,16
7,08
7,08
7,15
7,09
7,17
7,15
7,22
7,14
7,19
7,10
7,07
7,05
7,04
6,94
6,96
6,98
6,91
6,94
6,96
6,97
6,94
6,91
6,92
6,92
6,82
6,77
6,66
6,64
6,60
6,49
6,90
6,73
6,83
6,89
6,93
6,86
6,78
6,71
1998-12-11
1998-12-18
1998-12-25
1998-12-31
1999-01-08
1999-01-15
1999-01-22
1999-01-29
1999-02-05
1999-02-12
1999-02-19
1999-02-26
1999-03-05
1999-03-12
1999-03-19
1999-03-26
1999-04-02
1999-04-09
1999-04-16
1999-04-23
1999-04-30
1999-05-07
1999-05-14
1999-05-21
1999-05-28
1999-06-04
1999-06-11
1999-06-18
1999-06-25
1999-07-02
1999-07-09
1999-07-16
1999-07-23
1999-07-30
1999-08-06
1999-08-13
1999-08-20
1999-08-27
1999-09-03
1999-09-10
1999-09-17
1999-09-24
1999-10-01
1999-10-08
1999-10-15
1999-10-22
1999-10-29
1999-11-05
1999-11-12
1999-11-19
1999-11-26
1999-12-03
6,69
6,69
6,77
6,83
6,79
6,83
6,78
6,74
6,75
6,77
6,82
6,89
7,06
7,11
7,01
6,98
6,98
6,92
6,87
6,88
6,93
7,02
7,10
7,23
7,23
7,41
7,51
7,65
7,63
7,71
7,65
7,58
7,52
7,70
7,89
8,15
7,93
7,80
7,83
7,88
7,82
7,76
7,70
7,82
7,85
7,93
7,96
7,84
7,67
7,69
7,75
7,84
1999-12-10
1999-12-17
1999-12-24
1999-12-31
2000-01-07
2000-01-14
2000-01-21
2000-01-28
2000-02-04
2000-02-11
2000-02-18
2000-02-25
2000-03-03
2000-03-10
2000-03-17
2000-03-24
2000-03-31
2000-04-07
2000-04-14
2000-04-21
2000-04-28
2000-05-05
2000-05-12
2000-05-19
2000-05-26
2000-06-02
2000-06-09
2000-06-16
2000-06-23
2000-06-30
2000-07-07
2000-07-14
2000-07-21
2000-07-28
2000-08-04
2000-08-11
2000-08-18
2000-08-25
2000-09-01
2000-09-08
2000-09-15
2000-09-22
2000-09-29
2000-10-06
2000-10-13
2000-10-20
2000-10-27
2000-11-03
2000-11-10
2000-11-17
2000-11-24
2000-12-01
7,84
7,86
7,96
8,06
8,15
8,18
8,26
8,25
8,25
8,36
8,38
8,31
8,27
8,23
8,24
8,23
8,23
8,20
8,12
8,16
8,13
8,28
8,52
8,64
8,62
8,54
8,32
8,22
8,14
8,22
8,16
8,09
8,21
8,13
8,12
8,04
7,96
7,99
7,96
7,94
7,88
7,90
7,88
7,83
7,84
7,83
7,68
7,73
7,79
7,73
7,73
7,65
2000-12-08
2000-12-15
2000-12-22
2000-12-29
2001-01-05
2001-01-12
2001-01-19
2001-01-26
2001-02-02
2001-02-09
2001-02-16
2001-02-23
2001-03-02
2001-03-09
2001-03-16
2001-03-23
2001-03-30
2001-04-06
2001-04-13
2001-04-20
2001-04-27
2001-05-04
2001-05-11
2001-05-18
2001-05-25
2001-06-01
2001-06-08
2001-06-15
2001-06-22
2001-06-29
2001-07-06
2001-07-13
2001-07-20
2001-07-27
2001-08-03
2001-08-10
2001-08-17
2001-08-24
2001-08-31
2001-09-07
2001-09-14
2001-09-21
2001-09-28
2001-10-05
2001-10-12
2001-10-19
2001-10-26
2001-11-02
2001-11-09
2001-11-16
2001-11-23
2001-11-30
7,54
7,42
7,17
7,13
7,07
6,89
7,02
7,15
7,09
6,98
7,01
7,12
7,03
6,97
6,96
6,89
6,91
7,01
7,04
7,14
7,12
7,14
7,10
7,14
7,20
7,24
7,20
7,14
7,11
7,11
7,19
7,21
7,08
7,03
7,00
7,00
6,92
6,91
6,92
6,89
6,86
6,80
6,72
6,64
6,58
6,61
6,64
6,56
6,45
6,51
6,75
7,02
2001-12-07
2001-12-14
2001-12-21
2001-12-28
2002-01-04
2002-01-11
2002-01-18
2002-01-25
2002-02-01
2002-02-08
2002-02-15
2002-02-22
2002-03-01
2002-03-08
2002-03-15
2002-03-22
2002-03-29
2002-04-05
2002-04-12
2002-04-19
2002-04-26
2002-05-03
2002-05-10
2002-05-17
2002-05-24
2002-05-31
2002-06-07
2002-06-14
2002-06-21
2002-06-28
2002-07-05
2002-07-12
2002-07-19
2002-07-26
2002-08-02
2002-08-09
2002-08-16
2002-08-23
2002-08-30
2002-09-06
2002-09-13
2002-09-20
2002-09-27
2002-10-04
2002-10-11
2002-10-18
2002-10-25
2002-11-01
2002-11-08
2002-11-15
2002-11-22
2002-11-29
6,84
7,09
7,17
7,16
7,14
7,06
6,83
6,96
7,02
6,88
6,86
6,81
6,80
6,87
7,08
7,14
7,18
7,13
6,99
6,94
6,88
6,78
6,79
6,89
6,81
6,76
6,71
6,71
6,63
6,55
6,57
6,54
6,49
6,34
6,43
6,31
6,22
6,27
6,22
6,15
6,18
6,05
5,99
6,01
5,98
6,15
6,31
6,13
6,11
5,94
6,03
6,13
2002-12-06
2002-12-13
2002-12-20
2002-12-27
2003-01-03
2003-01-10
2003-01-17
2003-01-24
2003-01-31
2003-02-07
2003-02-14
2003-02-21
2003-02-28
2003-03-07
2003-03-14
2003-03-21
2003-03-28
2003-04-04
2003-04-11
2003-04-18
2003-04-25
2003-05-02
2003-05-09
2003-05-16
2003-05-23
2003-05-30
2003-06-06
2003-06-13
2003-06-20
2003-06-27
2003-07-04
2003-07-11
2003-07-18
2003-07-25
2003-08-01
2003-08-08
2003-08-15
2003-08-22
2003-08-29
2003-09-05
2003-09-12
2003-09-19
2003-09-26
2003-10-03
2003-10-10
2003-10-17
2003-10-24
2003-10-31
2003-11-07
2003-11-14
2003-11-21
2003-11-28
6,19
6,04
6,03
5,93
5,85
5,95
5,97
5,91
5,90
5,88
5,86
5,84
5,79
5,67
5,61
5,79
5,91
5,79
5,85
5,82
5,79
5,70
5,62
5,45
5,34
5,31
5,26
5,21
5,21
5,24
5,40
5,52
5,67
5,94
6,14
6,34
6,24
6,28
6,32
6,44
6,16
6,01
5,98
5,77
5,95
6,05
6,05
5,94
5,98
6,03
5,83
5,89
2003-12-05
2003-12-12
2003-12-19
2003-12-26
2003-12-31
2004-01-08
2004-01-15
2004-01-22
2004-01-29
2004-02-05
2004-02-12
2004-02-19
2004-02-26
2004-03-04
2004-03-11
2004-03-18
2004-03-25
2004-04-01
2004-04-08
2004-04-15
2004-04-22
2004-04-29
2004-05-06
2004-05-13
2004-05-20
2004-05-27
2004-06-03
2004-06-10
2004-06-17
2004-06-24
2004-07-01
2004-07-08
2004-07-15
2004-07-22
2004-07-29
2004-08-05
2004-08-12
2004-08-19
2004-08-26
2004-09-02
2004-09-09
2004-09-16
2004-09-23
2004-09-30
2004-10-07
2004-10-14
2004-10-21
2004-10-28
2004-11-04
2004-11-11
2004-11-18
2004-11-24
6,02
5,88
5,82
5,81
5,85
5,87
5,66
5,64
5,68
5,72
5,66
5,58
5,58
5,59
5,41
5,38
5,40
5,52
5,79
5,89
5,94
6,01
6,12
6,34
6,30
6,32
6,28
6,30
6,32
6,25
6,21
6,01
6,00
5,98
6,08
5,99
5,85
5,81
5,82
5,77
5,83
5,75
5,70
5,72
5,82
5,74
5,69
5,64
5,70
5,76
5,74
5,72
2004-12-02
2004-12-09
2004-12-16
2004-12-22
2004-12-29
2005-01-06
2005-01-13
2005-01-20
2005-01-27
2005-02-03
2005-02-10
2005-02-17
2005-02-24
2005-03-03
2005-03-10
2005-03-17
2005-03-24
2005-03-31
2005-04-07
2005-04-14
2005-04-21
2005-04-28
2005-05-05
2005-05-12
2005-05-19
2005-05-26
2005-06-02
2005-06-09
2005-06-16
2005-06-23
2005-06-30
2005-07-07
2005-07-14
2005-07-21
2005-07-28
2005-08-04
2005-08-11
2005-08-18
2005-08-25
2005-09-01
2005-09-08
2005-09-15
2005-09-22
2005-09-29
2005-10-06
2005-10-13
2005-10-20
2005-10-27
2005-11-03
2005-11-10
2005-11-17
2005-11-23
5,81
5,71
5,68
5,75
5,81
5,77
5,74
5,67
5,66
5,63
5,57
5,62
5,69
5,79
5,85
5,95
6,01
6,04
5,93
5,91
5,80
5,78
5,75
5,77
5,71
5,65
5,62
5,56
5,63
5,57
5,53
5,62
5,66
5,73
5,77
5,82
5,89
5,80
5,77
5,71
5,71
5,74
5,80
5,91
5,98
6,03
6,10
6,15
6,31
6,36
6,37
6,28
2005-12-01
2005-12-08
2005-12-15
2005-12-22
2005-12-29
2006-01-05
2006-01-12
2006-01-19
2006-01-26
2006-02-02
2006-02-09
2006-02-16
2006-02-23
2006-03-02
2006-03-09
2006-03-16
2006-03-23
2006-03-30
2006-04-06
2006-04-13
2006-04-20
2006-04-27
2006-05-04
2006-05-11
2006-05-18
2006-05-25
2006-06-01
2006-06-08
2006-06-15
2006-06-22
2006-06-29
2006-07-06
2006-07-13
2006-07-20
2006-07-27
2006-08-03
2006-08-10
2006-08-17
2006-08-24
2006-08-31
2006-09-07
2006-09-14
2006-09-21
2006-09-28
2006-10-05
2006-10-12
2006-10-19
2006-10-26
2006-11-02
2006-11-09
2006-11-16
2006-11-22
6,26
6,32
6,30
6,26
6,22
6,21
6,15
6,10
6,12
6,23
6,24
6,28
6,26
6,24
6,37
6,34
6,32
6,35
6,43
6,49
6,53
6,58
6,59
6,58
6,60
6,62
6,67
6,62
6,63
6,71
6,78
6,79
6,74
6,80
6,72
6,63
6,55
6,52
6,48
6,44
6,47
6,43
6,40
6,31
6,30
6,37
6,36
6,40
6,31
6,33
6,24
6,18
2006-11-30
2006-12-07
2006-12-14
2006-12-21
2006-12-28
2007-01-04
2007-01-11
2007-01-18
2007-01-25
2007-02-01
2007-02-08
2007-02-15
2007-02-22
2007-03-01
2007-03-08
2007-03-15
2007-03-22
2007-03-29
2007-04-05
2007-04-12
2007-04-19
2007-04-26
2007-05-03
2007-05-10
2007-05-17
2007-05-24
2007-05-31
2007-06-07
2007-06-14
2007-06-21
2007-06-28
2007-07-05
2007-07-12
2007-07-19
2007-07-26
2007-08-02
2007-08-09
2007-08-16
2007-08-23
2007-08-30
2007-09-06
2007-09-13
2007-09-20
2007-09-27
2007-10-04
2007-10-11
2007-10-18
2007-10-25
2007-11-01
2007-11-08
2007-11-15
2007-11-21
6,14
6,11
6,12
6,13
6,18
6,18
6,21
6,23
6,25
6,34
6,28
6,30
6,22
6,18
6,14
6,14
6,16
6,16
6,17
6,22
6,17
6,16
6,16
6,15
6,21
6,37
6,42
6,53
6,74
6,69
6,67
6,63
6,73
6,73
6,69
6,68
6,59
6,62
6,52
6,45
6,46
6,31
6,34
6,42
6,37
6,40
6,40
6,33
6,26
6,24
6,24
6,20
2007-11-29
2007-12-06
2007-12-13
2007-12-20
2007-12-27
2008-01-03
2008-01-10
2008-01-17
2008-01-24
2008-01-31
2008-02-07
2008-02-14
2008-02-21
2008-02-28
2008-03-06
2008-03-13
2008-03-20
2008-03-27
2008-04-03
2008-04-10
2008-04-17
2008-04-24
2008-05-01
2008-05-08
2008-05-15
2008-05-22
2008-05-29
2008-06-05
2008-06-12
2008-06-19
2008-06-26
2008-07-03
2008-07-10
2008-07-17
2008-07-24
2008-07-31
2008-08-07
2008-08-14
2008-08-21
2008-08-28
2008-09-04
2008-09-11
2008-09-18
2008-09-25
2008-10-02
2008-10-09
2008-10-16
2008-10-23
2008-10-30
2008-11-06
2008-11-13
2008-11-20
6,10
5,96
6,11
6,14
6,17
6,07
5,87
5,69
5,48
5,68
5,67
5,72
6,04
6,24
6,03
6,13
5,87
5,85
5,88
5,88
5,88
6,03
6,06
6,05
6,01
5,98
6,08
6,09
6,32
6,42
6,45
6,35
6,37
6,26
6,63
6,52
6,52
6,52
6,47
6,40
6,35
5,93
5,78
6,09
6,10
5,94
6,46
6,04
6,46
6,20
6,14
6,04
2008-11-26
2008-12-04
2008-12-11
2008-12-18
2008-12-24
2008-12-31
2009-01-08
2009-01-15
2009-01-22
2009-01-29
2009-02-05
2009-02-12
2009-02-19
2009-02-26
2009-03-05
2009-03-12
2009-03-19
2009-03-26
2009-04-02
2009-04-09
2009-04-16
2009-04-23
2009-04-30
2009-05-07
2009-05-14
2009-05-21
2009-05-28
2009-06-04
2009-06-11
2009-06-18
2009-06-25
2009-07-02
2009-07-09
2009-07-16
2009-07-23
2009-07-30
2009-08-06
2009-08-13
2009-08-20
2009-08-27
2009-09-03
2009-09-10
2009-09-17
2009-09-24
2009-10-01
2009-10-08
2009-10-15
2009-10-22
2009-10-29
2009-11-05
2009-11-12
2009-11-19
5,97
5,53
5,47
5,19
5,14
5,10
5,01
4,96
5,12
5,10
5,25
5,16
5,04
5,07
5,15
5,03
4,98
4,85
4,78
4,87
4,82
4,80
4,78
4,84
4,86
4,82
4,91
5,29
5,59
5,38
5,42
5,32
5,20
5,14
5,20
5,25
5,22
5,29
5,12
5,14
5,08
5,07
5,04
5,04
4,94
4,87
4,92
5,00
5,03
4,98
4,91
4,83
2009-11-25
2009-12-03
2009-12-10
2009-12-17
2009-12-24
2009-12-31
2010-01-07
2010-01-14
2010-01-21
2010-01-28
2010-02-04
2010-02-11
2010-02-18
2010-02-25
2010-03-04
2010-03-11
2010-03-18
2010-03-25
2010-04-01
2010-04-08
2010-04-15
2010-04-22
2010-04-29
2010-05-06
2010-05-13
2010-05-20
2010-05-27
2010-06-03
2010-06-10
2010-06-17
2010-06-24
2010-07-01
2010-07-08
2010-07-15
2010-07-22
2010-07-29
2010-08-05
2010-08-12
2010-08-19
2010-08-26
2010-09-02
2010-09-09
2010-09-16
2010-09-23
2010-09-30
2010-10-07
2010-10-14
2010-10-21
2010-10-28
2010-11-04
2010-11-11
2010-11-18
4,78
4,71
4,81
4,94
5,05
5,14
5,09
5,06
4,99
4,98
5,01
4,97
4,93
5,05
4,97
4,95
4,96
4,99
5,08
5,21
5,07
5,07
5,06
5,00
4,93
4,84
4,78
4,79
4,72
4,75
4,69
4,58
4,57
4,57
4,56
4,54
4,49
4,44
4,42
4,36
4,32
4,35
4,37
4,37
4,32
4,27
4,19
4,21
4,23
4,24
4,17
4,39
2010-11-24
2010-12-02
2010-12-09
2010-12-16
2010-12-23
2010-12-30
2011-01-06
2011-01-13
2011-01-20
2011-01-27
2011-02-03
2011-02-10
2011-02-17
2011-02-24
2011-03-03
2011-03-10
2011-03-17
2011-03-24
2011-03-31
2011-04-07
2011-04-14
2011-04-21
2011-04-28
2011-05-05
2011-05-12
2011-05-19
2011-05-26
2011-06-02
2011-06-09
2011-06-16
2011-06-23
2011-06-30
2011-07-07
2011-07-14
2011-07-21
2011-07-28
2011-08-04
2011-08-11
2011-08-18
2011-08-25
2011-09-01
2011-09-08
2011-09-15
2011-09-22
2011-09-29
2011-10-06
2011-10-13
2011-10-20
2011-10
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