Name
|
Type
|
Export (US dollars)
|
Index
(2005-01-01)
|
Real effective exchange rate index
RUB/USD
|
Index
(2005-01-01)
|
Index of industrial production
|
Index
(2005-01-01)
|
Nominal exchange rate
|
The average of daily returns
|
description of variables in the
statistical software Stata is:- aggregate export of Russian Federation_rate -
nominal exchange rate RUB/USD_production - index of industrial production in RF
_effective_exchange_rate - real effective exchange rate index RUB/USD
2.2 Empirical
methodology
order to estimate the impact of
nominal exchange rate volatility RUB/USD on Russian export it is essential to
make two steps: estimating the nominal exchange rate volatility, obtained from
ARCH model and building autoregressive models with distributed lags, based on
available data and estimated nominal exchange rate volatility.
. As it is mentioned above,
first of all, it is important to estimate nominal exchange rate volatility
RUB/USD by using ARCH model, which makes possible to investigate time-varying
volatility (the volatility, which changes over time) :
>0, 0< <1
ARCH model
the conditional variation (time-varying volatility) depends on the squares of the
errors in the previous periods (). It is crucial to mention that all
coefficients before ARCH parameter in this model must be positive and not be
more than one (0< <1) Moreover, the constant term
must be also positive. ARCH model was proposed by R.F. Engle in his article
“Autoregressive conditional heteroskedasticity with estimates of the variance
of United Kingdom inflation” (1982). Nowadays ARCH model is widely used for
various purposes of investigations of different financial time series,
including the estimating exchange rate volatility. The main attractive feature
of this model is that it does not neglect “news”. What is more, ARCH model pays
to attention to the clustering of volatility, when high volatility follows high
volatility and low volatility follows low volatility, which is rather common
for real economies.
2. The next step, according our
empirical methodology, is constructing autoregressive models with distributed
lags (ADL models) in order to analyze the direction of influence of nominal
exchange rate volatility RUB/USD, estimated by the method, described above, on
export of Russian Federation. Apart from nominal exchange rate volatility,
following variables are used as a explanatory variables in the ADL models:
Russian industrial production and real effective exchange rate RUB/USD. It is
expected that the industrial production has a positive impact on export,
because the growth of industrial production means that the competition in the
domestic market becomes tougher, encouraging the producers to expand export
activity. According to expectations, real effective exchange rate RUB/USD has
also a positive effect on Russian export, because, taking into account the
conception of traditional international trade theory, depreciation of the
national currency or growth of relative foreign price level (the ratio of
foreign price level and domestic price level) (growth of real effective exchange
rate RUB/USD) leads to the increase in export due to its reduction in price for
foreign consumers, and the decrease in import due to its rise in price for
domestic consumers. In the model current value of nominal exchange rate RUB/USD
volatility is not considered, given the fact that the exporters cannot react to
current volatility of nominal exchange rate, only to lags of this variable. The
empirical model, which is tested in this research, looks like:
- the value of Russian export at
the period t
- the value of Russian industrial
production at the period t
- the value of real effective
exchange rate RUB/USD at the period t
- nominal exchange rate volatility
RUB/USD at the period t-1 optimal structure should be defined by using
information criteria.
3. The final step, which should
be made, if we want to finish empirical analysis, is considering the effect of
reverse causality between values of export and nominal exchange rate
volatility. In order to overcome this difficulty, the method, which is
suggested in the article “Chickens, eggs, and causality, or which came
first?”(1988), is used. The core idea of this method is that, initially, it is
essential to build two regressions. In the first regression the current value
of export serves as a dependent variable, while the independent variables are
the lags of export and nominal exchange rate volatility. In the second
regression the opposite situation is observed: the dependent variable is the
current value of nominal exchange rate volatility and independent variables are
the same as for the first regression.
If the null
hypothesis that all coefficients before the lags of nominal exchange rate
volatility equals to null ( is accepted, it is possible to say
that the nominal exchange rate volatility does not cause changes in export. ,
we define the causality from export to exchange rate volatility.
If the null
hypothesis that all coefficients before the lags of export equals to null ( is accepted, it is possible to say
that the export does not cause changes in exchange rate volatility.
2.3 Descriptive
statistics
graphic of nominal exchange rate,
shown below, helps to demonstrate visually the existence and the magnitude of
exchange rate volatility from the first quarter of 2000 to the third quarter of
2014. this graph we can see that high volatility is near high volatility and
the low volatility is near low volatility. As a consequent, it is possible to
make following conclusion about clustering of volatility - visual information
provides us with the opportunity to use ARCH model for estimating nominal
exchange rate volatility RUB/USD.graph of other observed variables can be found
in Appendix B.
1
descriptive statistics of values of
economic parameters, used in the research, with the time span from the first
quarter of 2000 to the third quarter of 2014, are demonstrated below:
Table 2
It is possible to prove the
expectations about direction of impact of real effective exchange rate RUB/USD
and Russian industrial production on Russian export, described in empirical
methodology, by using correlation analysis:
Table 3
As it is seen from the preliminary
results, export and real effective exchange rate and export and industrial
production are positively linked.
3. Empirical
analysis
3.1 Stationarity of
variables
, it is really crucial to test time
series of logarithmic values of nominal exchange rate, real effective exchange
rate, industrial production and export for stationarity. Using non-stationary
time series may lead to “spurious regressions”.
values of
export:
Logarithmic values of real effective
exchange rate:
Logarithmic values of industrial
production:
Logarithmic values of nominal
exchange rate:
As it is seen from the obtained
results, none of the variables is stationary time-series, because the null
hypothesis that the time series contains the unit root is accepted at the
significance level of 1 % (The real effective exchange rate is a stationary
time series at the significance level of 5 %). In order to overcome the problem
of non-stationary time series, it is high time to shift to the analysis of the
first difference of investigated variables.first difference of logarithmic
values of export:
The first difference of logarithmic
values of real effective exchange rate:
The first difference of logarithmic
values of industrial production:
All in all, according to results of
tests, the problem of non-stationary time series is resolved for export, real
effective exchange rate, industrial production, nominal exchange rate, because
the first differences of these variables are stationary time series at the
significance level of 1 % (The null hypothesis that these new obtained time
series contain the unit root is rejected at the significance level of 1 %).
.2 Estimating nominal exchange rate
volatility by using ARCH model
, ARCH model is constructed for
further estimation of nominal exchange rate volatility RUB/USD, it is essential
to test the existence of ARCH effects for the nominal exchange rate RUB/USD. In
order to achieve this aim, LM test is conducted.
The obtained results show that the
null hypothesis that there are no ARCH effects for the nominal exchange rate
RUB/USD is rejected at the significance level of 1 %. Consequently, ARCH
effects are observed for the nominal exchange rate RUB/USD. Now it is possible
to build ARCH model.
The coefficient before ARCH
parameter is significant at the significance level of 1 %, while it is also
positive. This intermediate result allows to explain continue estimation of
exchange rate volatility.’s test the obtained by using ARCH model time series
of estimates of nominal exchange rate volatility RUB/USD for stationarity:
The null hypothesis that this time
series contains the unit root is rejected at the significance levelof 1 %.
Respectively, the estimated exchange rate volatility is a stationary rime
series and it is possible to continue empirical analysis.graphic of nominal
exchange rate volatility RUB/USD, obtained by using ARCH model, during the
period from the first quarter of 2000 to the third quarter of 2014, looks:
2
3.3 Constructing ADL
regressions
of all, it is essential to build
regression, which incorporates following independent variables: the first lags
of export, industrial production, real effective exchange rate and volatility,
as well as the current values of industrial production and real effective
exchange rate (In the model only the first lags are used, because the optimal
structure of the lags involves only the first lags, according to information
criteria (Appendix A)). As a result, we obtain the following model:
From this table it can be inferred
that the coefficient before the current values of industrial production, as
well as the coefficient before the first lag volatility are significant,
because the null hypothesis that coefficients before these variables equal to
null. On the other hand, other coefficients are insignificant. Now it would be
an excellent idea to construct regression, incorporating the first lags of
export and volatility and the current values of real effective exchange rate and
industrial production
In the obtained model all
coefficients are significant. The impact of industrial production and real
effective exchange rate turns to be positive, as it has been expected. The
growth of industrial production leads to increase in export, while the rise of
real effective exchange rate causes the increase in export. The value of export
in the previous period (the first lag of export) positively affects the current
value of export, which seems rather evident. The positive sign of the
coefficient before the first lag of nominal exchange rate volatility means that
the obtained result is not intuitive: if the nominal exchange rate volatility
RUB/USD goes up, the growth of export will happen.
.4 Determination of causality
between export and volatility
spite of the fact that the positive
impact of exchange rate volatility in the previous period on current value of
export is obtained, this finding does not withdraw the question causality
between exchange rate volatility and export: not only exchange rate volatility
causes changes in export, but also export causes changes in exchange rate
volatility. In order to find an answer to this question it is essential to
method, described above: construction of two regressions with export and
exchange rate volatility as dependent variables and the first lags of exchange
rate volatility and export as independent variables.first regression with
export as a dependent variable:
The second regression with exchange
rate volatility as a dependent variable:
Taking into account the second
regression with the exchange rate volatility as a dependent variable, it is
remarkable that he first lag of values of export have a negative impact on
current exchange rate volatility. This interesting result can be explained so:
more closed economies required larger changes in exchange rates in order to
achieve the adjustments of balance of payments (The ratio export and GDP
(export/GDP) can be considered as a measure of openness of the economy)
(Canales-Kriljenko & Habermeier, 2004). What is more, other explanations
are also possible.these two regressions it can be concluded that not only the
exchange rate volatility in the previous period has an impact on export in the
current period, but also the export in previous period has an influence on
exchange rate volatility in the current period. Therefore, it is impossible to
make an inference about the unambiguous direction of the effect of exchange
rate volatility on export, because the both influence of the first lag of
exchange rate volatility on current export and impact of the first lag of
export on current exchange rate volatility.
4. Future research
the fact that the result is
obtained, it is essential to note what might be done in this area in the
future. First of all, it would be a good idea to investigate disaggregated data
of various branches of the national economy of Russian Federation (agriculture,
food industry, light industry etc). In this case the influence of each
variable, investigated in this research, for every sector. It is rather
plausible that the influence of exchange rate volatility is different for
different branches or is significant for some sectors and insignificant for
others.is more, the obtained model can be improved by adding the determinants
of export that are not used in this work. For instance, investigating the role
of variables, related to government influence on export: subsidies to
companies, exporting goods.into consideration that Russian government shifted
from fixed to floating exchange rate system at the end of 2014, it would be
interesting to conduct analogical research, but using future data in order to
answer the question: does the influence of exchange rate volatility change, in
the light of the larger exchange rate fluctuations.
Conclusion
work represents an empirical
research of the impact of nominal exchange rate volatility RUB/USD on export of
Russian export by using the time series of real effective exchange rate RUB/USD,
nominal exchange rate RUB/USD, expot of Russian Federation and Russian
industrial production during approximately fourteen years: from the first
quarter of 2000 to the third quarter of 2014. In order to estimate nominal
exchange rate volatility, ARCH model is applied. The obtained autoregressive
model with distributed lags tells us that the value of estimated nominal
exchange rate volatility in the previous period positively influence the export
in the current period, as well as other variables: current values of real
effective rate and industrial production and the first lag of export have an
expected positive effect on current export. On the other hand, it is defined
that the first lag of export affects the current exchange rate volatility.
Consequently, the mutual influence of export and exchange rate volatility is
observed. This fact can explain, in addition to other interpretations, the
positive impact of the nominal exchange rate volatility RUB/USD on export of
Russian Federation. Nevertheless, it would be a good idea for our Central Bank
not to spend great efforts on stabilization of the exchange rate RUB/USD, but
concentrate on stimulating economic growth in our country by reducing interest
rates in order to increase private investments. However, it is clear that it is
essential to conduct further research in order to find the most effective
policy of Central Bank for achieving maximal economic result for Russian
Federation.
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. Economic Data Federal
Reserve Bank of St. Louis
rate volatility
autoregressive export
Appendix A
criteria for the model,
incorporating only the first lags
Information criteria for the model,
incorporating the first two lags
Information criteria for the model,
incorporating the first three lags
Appendix B
of export during the observed period
of real effective exchange rate
RUB/USD during the observed period
Graph of industrial production
RUB/USD during the observed period