Page 110 - Azerbaijan State University of Economics

THE JOURNAL OF ECONOMIC SCIENCES: THEORY AND PRACTICE, V.77, # 1, 2020, pp.100-112

5. DISCUSSION
A descriptive statistical analysis of employment data alone does not provide the full
picture of the Dutch disease theory; however, it is a useful means to begin to
conceptualize its presence. To clarify the causal relationship between the booming
and lagging sectors, a model approach with more precise diagnostic adjustments is
necessary. Moreover, real wage and output data should be linked together to paint a
more detailed picture. Accordingly, future research related to Dutch disease in
Azerbaijan should employ econometric investigations alongside meta-structural
approaches, such as the resource curse hypothesis and institutional evaluations.
Deconstructing the non-tradable sectors and proper classification from the point of
exports and imports could shed more light on the effects of Dutch disease in
Azerbaijan. As Corden (1984) indicates, not every tradeable product is exported by
the country. In the background of booming and lagging sectors, the Dutch disease
can be easily misunderstood if highly aggregated data is used. Thereby, correlation
analysis is a weak estimation of the power and significance between the selected
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variables (also can be seen from the low R values, which indicates to use alternative
approaches). Without a sub-sectoral analysis of output and international trade, it is
difficult to conclude the existence of the Dutch disease hypotheses in an economy.

6. CONCLUDING REMARKS
This paper investigated the descriptive properties of the statistical data regarding
employment in Azerbaijan within a Dutch disease framework. The research question
adopted was as follows: is the distribution of the statistical data in employment covering
the period between 2000-2018 consistent with the Dutch disease hypotheses? The main
results of statistical analysis analyzed the presence of the phenomenon, including REER
appreciation, high shares in the booming sector in the output, and exports, while
manufacturing and agriculture as lagers contracted their share. The results indicated that
the resource movement effect of the Dutch disease could not be observed in mining
employment, because, being a capital-intensive sector, it did not experience any
extraordinary employment levels. On the contrary, it decreased over the time period
examined. However, the negative growth rates of the non-oil tradable sectors and the
rapid increase in services employment fit the spending effect of the Dutch disease
model. While the scatter plot matrix demonstrated a positive relationship between
REER and mining, manufacturing and agriculture, and negative relationship between
REER and services, Pearson’s R correlation identified a strong, positive and significant
connection between the variables that support the Dutch disease effects. However, on a
descriptive level, this investigation should be treated illustrative rather than conclusive.

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