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Economic Policy Papers
Factors that affect productivity and economic
growth of European economies
Theofanis Mamuneas
Elena Ketteni
Frederick University
Department of Economics
University of Cyprus
No. 10-16
December 2016
Publication Editor: Christos Koutsampelas
ERC Sponsors (in alphabetical order)
Central Bank of Cyprus
Directorate General for European Programmes, Coordination and Development
Economics Department, University of Cyprus
Ministry of Finance
Ministry of Labour, Welfare and Social Insurance
University of Cyprus
Disclaimer: the views expressed in the Economic Policy Papers and Economic Analysis
Papers are of the authors and do not necessarily represent the ERC.
ii
Factors that affect productivity and economic growth of
European economies
Elena Ketteni* and Theofanis Mamuneas
ABSTRACT
The wake of 2008 financial crisis and the current euro area crisis has highlighted the
importance of productivity growth and competitiveness. “Persistent losses in
competitiveness and mounting external imbalances not only increase the economic
and financial vulnerability of individual countries, but given the strong financial and
trade interconnectedness of the euro area countries may also hinder the functioning
of the euro area as a whole”. So, a key driving force for the welfare and gains in
income is how productive and competitive a country is. High productivity reduces
average costs and in the long-run reduces product prices making the economy more
competitive. Productivity improvement is challenging country’s capabilities to improve
their economic competitiveness. It is generally acknowledged that, nowadays, due to
the crisis, the pressure to maintain growth is felt most. Policy makers are challenged
to develop strategies to foster growth.
To support decision makers this study focuses on the factors that influence
productivity and economic growth. Literature and theory point to various factors that
affect productivity such as: taxes (income, company), innovation, regulations, R&D
expenditure, and investment in information and communication technologies,
educational attainment/human capital, patents, foreign direct investment and
infrastructure expenditures.
For this paper we have collected data on 30 European countries for the period 1996
to 2014. We used the gross value added, labor and capital to construct an index of
productivity growth. This study focuses on factors that influence productivity and
economic growth in various countries and to do so we have collected measures such
as the: R&D expenditure (% of GDP), FDI net inflows and outflows (% of GDP),
Gross enrolment ratios (primary, secondary and tertiary), Patent applications
(number), ICT (% of GDP and growth rate). The results from our analysis, suggest
that both expenditures (R&D and ICT) have positive impacts on TFP growth, as well
as patent applications. Therefore higher innovation captured by R&D, ICT and
patents causes an upward shift in the productivity. Increased FDI inflows do not
seem to affect TFP in our analysis. Finally, the variables used to capture human
capital show that: gross enrolments in primary education have a negative and
significant effect on TFP growth, secondary enrolments appear insignificant and
tertiary enrolments influence positively and significantly the TFP growth rate of the
previously mentioned countries country. Based on that when the number of people
iii
entering tertiary education increases (suggesting higher human capital) this leads to
a positive effect on TFP growth.
Keywords: productivity, economic growth, ICT capital, R&D expenditures, human
capital, innovation
* Corresponding author, e-mail: [email protected]
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CONTENTS
1. Introduction ............................................................................................... 9
2. Methodology and Data ........................................................................... 13
2.1 Model Specification ................................................................... 13
2.2 Data Description and Construction ............................................ 14
Empirical Estimation ................................................................................... 16
Conclusion .................................................................................................. 17
References ................................................................................................. 18
vi
Παράγοντες που επηρεάζουν την παραγωγικότητα και οικονομική
ανάπτυξη των Ευρωπαϊκών οικονομιών
Έλενα Κεττένη και Θεοφάνης Μαμουνέας
ΠΕΡΙΛΗΨΗ
Η οικονομική κρίση του 2008 έφερε στο προσκήνιο τη σημαντικότητα της
παραγωγικότητας και της ανταγωνιστικότητας μιας Ευρωπαϊκής οικονομίας. Το
κλειδί για την ανάπτυξη, ευημερία και αύξηση του εισοδήματος μιας χώρας βρίσκεται
στο πόσο παραγωγική είναι. Η υψηλή παραγωγικότητα οδηγεί σε μείωση του μέσου
κόστους παραγωγής και των τιμών των προϊόντων κάνοντας τη χώρα πιο
ανταγωνιστική. Είναι ευρέως γνωστό ότι τα τελευταία χρόνια υπάρχει μεγάλη πίεση
στις Ευρωπαϊκές χώρες για οικονομική ανάπτυξη. Οι υπεύθυνοι πολιτικής βρίσκονται
αντιμέτωποι με την πρόκληση να δημιουργήσουν στρατηγικές που θα οδηγήσουν
στην ανάπτυξη των χωρών τους. Ένας τρόπος για να το πετύχουν αυτό είναι η
αύξηση της παραγωγικότητας της χώρας.
Η μελέτη αυτή, εξετάζει παράγοντες που επηρεάζουν την παραγωγικότητα και άρα
την οικονομική ανάπτυξη μιας χώρας. Στην πρόσφατη βιβλιογραφία υπάρχουν
πολλοί παράγοντες που επηρεάζουν την παραγωγικότητα όπως: φόροι
(εισοδήματος, επιχειρήσεων), επενδύσεις σε νέες καινοτομίες, νέες τεχνολογίες της
πληροφορικής, εκπαίδευση, έρευνα και ανάπτυξη, πατέντες, άμεσες ξένες
επενδύσεις, κανονισμοί που διέπουν την αγορά προϊόντος και εργασίας και
επενδύσεις σε δημόσιες υποδομές με θετικές επιδράσεις.
Για τη μελέτη αυτή έχουν συλλεχθεί στοιχεία για 30 Ευρωπαϊκές χώρες για την
περίοδο 1996-2014. Αρχικά χρησιμοποιώντας το προϊόν (ακαθάριστη προστιθέμενη
αξία), το κεφάλαιο και την εργασία κατασκευάστηκε ο ρυθμός ανάπτυξης της
παραγωγικότητας για κάθε οικονομία. Μετά συλλέχθηκαν στοιχεία για διάφορους
παράγοντες που μπορεί να επηρεάσουν το ρυθμό αυτό. Συγκεκριμένα, θέλουμε να
δούμε ποιοι παράγοντες από αυτούς επηρεάζουν θετικά την παραγωγικότητα μιας
χώρας. Η οικονομετρική ανάλυση έδειξε ότι σημαντική θετική επίδραση στο ρυθμό
της παραγωγικότητας έχουν οι επενδύσεις σε έρευνα και ανάπτυξη, οι νέες
τεχνολογίες της πληροφορικής και ο αριθμός των πατέντων σε μια χώρα, ενώ οι
άμεσες ξένες επενδύσεις δεν επηρεάζουν. Οι εγγραφές ατόμων σε πρωτοβάθμια
εκπαίδευση επηρεάζουν αρνητικά, σε δευτεροβάθμια δεν επηρεάζουν καθόλου και
σε τριτοβάθμια (ανώτερη) εκπαίδευση επηρεάζουν θετικά και σημαντικά την
παραγωγικότητα μιας χώρας. Αυτό μας υποδεικνύει τη σημαντικότητα του
ανθρώπινου κεφαλαίου τόσο για την αύξηση της παραγωγικότητας, όσο και για την
οικονομική ανάπτυξη μιας χώρας. Λαμβάνοντας υπόψη αυτούς τους παράγοντες, οι
ασκούντες πολιτικής μπορούν να επηρεάσουν την παραγωγικότητα και την
οικονομική ανάπτυξη μιας οικονομίας.
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1. Introduction
The wake of 2008 financial crisis and the current euro area crisis has highlighted the
importance of productivity growth and competitiveness. “Persistent losses in
competitiveness and mounting external imbalances not only increase the economic
and financial vulnerability of individual countries, but given the strong financial and
trade interconnectedness of the euro area countries may also hinder the functioning
of the euro area as a whole” 1. So, a key driving force for the welfare and gains in
income is how productive and competitive a country is.
Productivity is a measure of economic efficiency which shows how effectively
economic inputs are converted into output. “Productivity is commonly defined as a
ratio of a volume measure of output to a volume measure of input use. While there is
no disagreement on this general notion, a look at the productivity literature and its
various applications very quickly reveals that there is neither a unique purpose for
nor a single measure of productivity”, (Paul Schreyer, OECD, 2001).
National productivity estimates are of special importance because they are an input
into many aspects of public policy making. For instance, the national monetary
authorities consider national productivity growth estimates in making decisions about
acceptable amounts of price inflation. Productivity also affects exchange rates
employment, investment and consumption. Bearing this in mind, productivity growth
is an essential determinant for monetary policy 2. There is evidence that increases in
productivity are associated with low inflationary pressures and increases
competitiveness.
High productivity reduces average costs and in the long-run reduces product prices
making the economy more competitive. Nothing contributes more: to reduction of
poverty, to increases in leisure, and to the country’s ability to finance education,
public health, environment and the arts” (Alan Blinder and William Baumol 1993,
Economics: Principles and Policy, Harcourt Brace Jovanovich, San Diego, p. 778).
OECD report (2001) states also that increases in productivity are associated with
higher technical change or according to Grilliches (1988) better ways to convert
resources into outputs, higher efficiency (movements towards best practice in order
1
See ECB (2012). Working paper series 1431, Productivity in the Euro Area, Any evidence of
convergence?
2
For more details regarding productivity and monetary policy see ECB 2008 Monthly Bulletin (Jan
2008)
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to achieve maximum amount of output that is physically achievable with current
technology and given inputs, Diewert and Lawrence, 1999) and real cost savings in
production (Harberger, 1998).
The two most widely used measures of productivity are those of Total Factor
Productivity (TFP) and Labour Productivity (LP). But these measures are not
independent of each other. Total-factor productivity (TFP), also called multi-factor
productivity and used in our analysis, is a variable which captures the part of real
GDP growth which is unexplained by the contributions from labour and capital. It
shows how productively combined labor and capital inputs are used to generate
GDP. TFP growth reflects phenomena such as advances in general knowledge,
advantages of particular organizational structures or management techniques,
reduction in inefficiency and reallocations of resources to more productive uses. TFP
cannot be measured directly. Instead it is a residual, often called the Solow residual,
which accounts for effects in total output not caused by inputs.
Productivity improvement is challenging country’s capabilities to improve their
economic competitiveness. It is generally acknowledge that nowadays, due to the
crisis, the pressure to maintain growth is felt most. Policy makers are challenged to
develop strategies to foster growth. To support decision makers this study focuses
on the factors that influence productivity and economic growth. Literature and theory
point to various factors such as: income taxes, innovation, regulations R&D
expenditure and educational attainment among other (Eichler et. al., 2006; Havik et.
al., 2008). Specifically productivity is affected by, income and company taxes (tax on
investment) with negative effects on productivity growth. That is, higher taxes reduce
productivity growth. The income taxes appear to have a stronger and bigger impact.
Tax burden on investment and on highly qualified employees both influence
productivity growth negatively. This is important for policy considerations, along with
the fact that tax on employees has the strongest negative impact.
More innovation 3 increases productivity growth. Available innovation resources
(indicators such as: R&D expenditure share of GDP, labor force with secondary or
tertiary degree, human capital, ICT intensive technology) positively influence
economic growth. But sometimes the effect of these appears to be low. Maybe the
reason is that these do not reflect the more important kinds of innovation resources
3
By innovation we mean technological knowledge, process of creation, accumulation and diffusion or
adoption of knowledge.
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and also fostering innovation is not the quick and easy policy solution to solve all
growth problems. Moreno and Surinach (2014) indicate a positive role of innovation
adoption in fostering economic progress when it is fostering competitiveness,
productivity and job creation.
Product and labor market regulations both have a mixed effect (positive and
negative) on productivity and GDP growth. Specifically, labour market regulations
have a positive impact on productivity growth but their general effect depends on the
type of regulation; i.e. minimum wages affect only the less qualified labor. So
sometimes the overall effect on GDP (not just productivity) is found to be negative.
Product marker regulations generally have a negative effect on growth, even though
there is no conclusion that this effect does not vary.
Another factor found in the literature that affects productivity is investment.
Expenditures on tangible assets, education, training and other human capital
accumulation as well as R&D, ICT and public infrastructure play an important role in
the growth of a country, even though their precise effect on productivity differs
(Stiroh, 2001). Also openness to trade was found to have a positive effect on total
factor productivity growth. Openness was found to promote a higher standard of
living, while countries that pursue greater outward orientation can experience faster
economic growth (Miller and Upadhyay, 2002). The literature suggests that among
the most important determinants of productivity growth are education, health,
infrastructure, imports, institutions, openness to trade, financial development,
absorptive capacity, human capital, R&D expenditures and ICT, intangibles
(Isaksson, 2007; Bart van Ark, 2014).
Achieving sustainable growth is challenging especially in Europe. Economic growth
results from competitiveness. But EU competitiveness is weakened by both internal
(high cost business environment with an ageing and relative expensive labor force,
weakened innovation, high debt levels) and external (the financial system is not able
to attract enough investment) factors.
Still the EU has the potential for growth but needs to initiate the right reforms to
boost its competitiveness. Creating new business opportunities would allow firms to
invest more increasing their competitiveness and fostering growth. Investment in
education, enhancing the movement of highly skilled workers (highly skilled
migration), create the conditions for higher public and private investment by
encourage the more business friendly taxation. Other factors include: investment in
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infrastructure; innovation; better access to finance; smart use of public funds; intraEU trade; and a single market for energy. Improve the general framework of EU
policy by overcoming fiscal and budgetary freeriding and strengthening financial
market 4.
The European Investment Bank (EIB, 2011) stressed that Europe’s need for
productivity growth has become most pressing against problems faced by
economies such as debt and slowdown in labor supply.
The EIB suggests that:
o Governments should embrace domestic and international competition by
dismantling anti-competitive product marker regulations especially in services.
o Private and public R&D should feature high on the policy agenda and their
effectiveness should be enhanced by removing overly protective elements of
the patent system.
o Education attainment and quality as well as life-long learning should be
fostered and more emphasis put on ICT. Investments are needed in more
profitable areas.
o Productivity enhancing resources require lower employment protection and
stronger incentives for regional and sectoral mobility
The European Central Bank (ECB, Occasional Paper 53, 2006) examined
productivity developments in the euro area and they compared it with that of the US.
They studied the period spanning from 1980-2005 and they found that labour
productivity growth since mid-1990’s has fallen while in US it rose during the same
period. That decline was due to lower capital deepening (especially ICT capital) and
lower total factor productivity growth.
The ECB (Occasional Paper 72, 2007)
investigates also the role of financial systems in productivity, innovation and growth.
They suggest that there are ways to improve the financial markets performance in
Europe and by that to increase the contribution of financial system to productivity,
innovation and growth. The improvement of corporate governance, legal systems in
resolving conflicts in financial transaction and some structural features of the
European bank sectors are the most robust conclusions that these paper presents.
Finally, ECB (Working Paper 1431, 2012) studied whether productivity convergence
has taken place among euro area countries, with the results suggesting that no
4
Lighthouse Europe (2015), study on the key factors affecting the future growth of Europe prepared
for EESC.
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convergence exist at the aggregate level whether at the sectoral level there are only
small indications. It also concluded that highly educated workforce and investment in
R&D are positive determinants for productivity growth whereas higher regulatory
burden pushing productivity growth down.
To support decision makers this study focuses on the factors that influence
productivity and economic growth in various countries. The next section presents the
methodology and data used for the construction of TFP. In the sections that follow
we have the results and the final section concludes.
2. Methodology and Data
In this section we present the construction of the productivity indices and the data
used in our analysis.
2.1 Model Specification
Productivity, also known as TFP or Multi-Factor Productivity, is computed using the
Growth Accounting framework (Solow, 1957). Growth Accounting provides a suitable
framework for identifying individual factors of growth and summarising them in a
convenient way. It provides a useful framework for analyzing observed output growth
into components associated with changes in factor inputs and a residual. This
residual is known as Total Factor Productivity or Multifactor productivity.
The Growth Accounting framework is empirically motivated and can be seen as a
first attempt to understand the long-term growth process. It essentially implies
breaking down observed real GDP growth into the contributions from pertinent factor
growth such as labor, capital and technology. Growth accounting provides a residual
measure of TFP growth, which is in fact an index number and depends on the
functional form of the production function used.
Specifically, Solow’s (1957) seminal paper provides a convenient context for
introducing the basics of growth accounting, which has influenced numerous
subsequent growth accounting studies. Following his notion, we define a production
function as:
𝑌 = 𝐹�𝐾, 𝐿, 𝐴�,
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where Y is the quantity of output, K is the capital input; L is the labor input and A the
level of technology (TFP). Differentiating with respect to time and dividing by Y
(rearranging in terms of growth rates)
𝑦� =
𝜕𝜕 𝐾
𝜕𝜕 𝐿
𝜕𝜕 𝐴
𝑘� +
𝑙̂ +
𝐴̂
𝜕𝜕 𝑌
𝜕𝜕 𝑌
𝜕𝜕 𝑌
(1)
𝑑𝑑
where (.�) stands for the growth rate e.g. 𝑥� = 𝑑𝑑 /𝑋. Then the rate of TFP change or
Solow residual 𝑇� is calculated as a residual:
𝑇� =
𝜕𝜕 𝐴
𝜕𝜕 𝐾
𝜕𝜕 𝐿
𝐴̂ = 𝑦� −
𝑘� −
𝑙̂
𝜕𝜕 𝑌
𝜕𝜕 𝑌
𝜕𝜕 𝑌
(2)
Equation (2) is however impractical since the marginal product of capital,
𝜕𝜕
𝜕𝜕
𝜕𝜕
and
labour,𝜕𝜕 inputs are unobservable. But, assuming that firms maximize profits then
the social marginal products must be equal to the observed factor prices. Therefore,
equation (2) becomes:
𝜕𝜕 𝐴
𝐴̂ = 𝑦� − 𝑠𝐾 𝑘� − 𝑠𝐿 𝑙̂ = 𝑇� (3)
𝜕𝜕 𝑌
where (^) denotes again growth rate and si indicates the output shares of capital and
labor. This framework grew phenomenally from 1957 and was extended and applied
in various empirical studies. Further, in this paper it is assumed that Solow residual
it depends on variables z that might influence productivity and the exogenous
technical change. Therefore (3) becomes
𝑇� = 𝛼 + 𝛽 𝑧̂ (4)
2.2 Data Description and Construction
For our methodology one needs data for the prices and quantities of both the output
and the inputs. We obtained relevant data from several publications of Eurostat and
the European Commission. The data cover the period 1995 to 2014. The countries
included in our analysis are: Belgium, Bulgaria, Czech Republic, Denmark,
Germany, Estonia, Ireland, Greece, Spain, France, Italy, Cyprus, Latvia, Lithuania,
Luxembourg, Hungary, Malta, Netherlands, Austria, Poland, Portugal, Romania,
Slovenia, Slovakia, Finland, Sweden, UK, Norway, Switzerland and Iceland. All
prices are expressed in constant Euros of year 2000. The measure is billions of
Euros.
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The variables used for our analysis are: Gross Value Added in current prices and
constant 2000 prices, Employees (total and self employees), Total hours worked
(man hours, again for total and for self employees), investment in current prices and
in 2000 prices and Compensation of employees.
For the construction of the output variable, we use the value added in current prices
(used as the value of output), along with the value added in constant prices
(considered as the quantity of output). Dividing current with constant prices, the price
of output is obtained. For labor, necessary data are the price and quantity of labor.
The compensation of employees was used as the value of labor, adjusted to include
the self employees, a procedure followed also by the European Central Bank.
Having the value of labor and hours worked (again adjusted to include the self
employees) the price of labor was obtained, which was transformed in order to be
expressed in 2000 prices. Combining labor price and labor value one can derive the
quantity of labor in 2000 prices.
Investments, in current and constant prices, were used in order to construct the
capital stock. The value of capital was obtained using the value added in current
prices and the value of labor. The perpetual inventory method was followed with a
constant depreciation rate of 5%, to get the quantity of capital. For the initial value
(initial period t = 0) of the quantity of capital we use the initial capital stock obtained
from the European Commission data.
Following Christensen, Cummings and Jorgenson (1981) and Jorgenson and
Nishimizu (1978) in order to be able to compare countries, we require comparable
measures of factor inputs and output. To achieve comparability in measuring output
and factor inputs one needs to employ purchasing power parities (PPP) of output,
capital and labor for all the countries under consideration. Therefore, all price and
quantity data are expressed in constant 2000 Euros and are PPP adjusted.
Using the above inputs and output we construct the index of TFP growth based on
equation (3). The TFP growth is constructed as output growth minus a weighted sum
of the growth of all inputs.
For the variables z that might influence productivity we have collected additional data
from OECD, WDI (World Development Indicators) and Eurostat, for various
countries. We have collected measures such as the: R&D expenditure (% of GDP),
FDI net inflows and outflows (% of GDP), Gross enrolment ratios (primary,
15
secondary and tertiary), Patent applications (number), ICT (% of GDP and growth
rate).
Empirical Estimation
Using the variables z, mentioned above in the data section, we will examine the
relationship between the multifactor productivity and factors that appear in the
literature to influence productivity for a set of European countries. For our estimation
equation (4) becomes:
𝑇� = 𝛼 + � 𝑎𝑖 𝐷𝑖 + � 𝑎𝑡 𝐷𝑡 + 𝛽 𝑧̂
𝑖
𝑡
Time and country dummies (𝐷𝑡 , 𝐷𝑖 ) are also included in our regressions to capture
differences in countries and time. Specific F-tests suggested that the dummy
variables are jointly significant and should be included in our models. Results are
presented in Table 1.
Table 1: Empirical Results
VARIABLES
ESTIMATES
Rd percentage of GDP
0.0347**
(0.0043)
0.0013
(0.0009)
-0.0015***
(0.0008)
-0.0002
(0.0004)
0.00005**
(0.00001)
0.0247**
(0.0084)
0.0065*
(0.0011)
0.125***
(0.0743)
Foreign Direct Investment
Gross enrolment ratio primary
Gross enrolment ratio secondary
Patent applications
ICT percentage of GDP
Gross enrolment ratio tertiary
Constant
Observations
R-squared
308
0.377
Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1
In order to capture the innovation effects on TFP growth, we have used variables
such as R&D and ICT expenditures as a % of GDP, Patent applications and FDI
inflows. The results of Table 1 suggest that all our variables appear significant
16
except the FDI inflows. Both expenditures (R&D and ICT) have positive impacts on
TFP growth. Increasing investment in R&D and ICT technologies will cause an
increase in the TFP growth of a country. Finally, patents also have a positive, but
smaller, effect on TFP growth, so increases the number of patent applications within
a country also positively influences its TFP growth rate.
Also, in Table 1 shows the effect from human capital approximated by gross
enrolment ratios (%). The variables used to capture human capital show that: gross
enrolments in primary education seem to have a negative and significant effect on
TFP growth, secondary enrolments appear insignificant and tertiary enrolments
influence positively and significantly the TFP growth rate of a country. More people
entering tertiary education (suggesting higher human capital), there is a positive
effect on TFP growth.
Conclusion
Productivity
growth
is
an
essential
contributor
of
economic
growth
and
competitiveness in a country; the pressure to increase growth is strongly felt
nowadays. The literature and theory point to various factors that affect productivity
and this can support decision makers, with regards to achieving productivity growth.
This study focuses on factors that influence productivity and economic growth in
various countries: Belgium, Bulgaria, Czech Republic, Denmark, Germany, Estonia,
Ireland, Greece, Spain, France, Italy, Cyprus, Latvia, Lithuania, Luxembourg,
Hungary, Malta, Netherlands, Austria, Poland, Portugal, Romania, Slovenia,
Slovakia, Finland, Sweden, UK, Norway, Switzerland and Iceland. To do so we have
collected measures such as the: R&D expenditure (% of GDP), FDI net inflows and
outflows (% of GDP), Gross enrolment ratios (primary, secondary and tertiary),
Patent applications (number), ICT (% of GDP and growth rate) for the period 20002014.
The results from our analysis, suggest that both expenditures (R&D and ICT) have
positive impacts on TFP growth, as well as patent applications. Therefore higher
innovation captured by R&D, ICT and patents causes an upward shift in the
productivity. Increased FDI inflows do not seem to affect TFP in our analysis. Finally,
the variables used to capture human capital show that: gross enrolments in primary
education have a negative and significant effect on TFP growth, secondary
17
enrolments appear insignificant and tertiary enrolments influence positively and
significantly the TFP growth rate of the previously mentioned countries country.
Based on that when the number of people entering tertiary education increases
(suggesting higher human capital) this leads to a positive effect on TFP growth.
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18
Schreyer, P. 2001, Measuring productivity, OECD publications.
Solow, R. M. 1957, Technical change and the aggregate production function, Review
of Economics and Statistics, volume 39(3), pages 312-320.
Stiroh, K. J. 2001, What drives productivity growth?, FRBNY Economic Policy
Review, March.
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RECENT ECONOMIC POLICY/ANALYSIS PAPERS
09-16
Eliophotou, M. and N. Pashourtidou, “ Low Socioeconomic Status
Students in Higher Education: Entry, Academic Attainment and
Earnings Expectations”, December 2016.
08-16
Theodotou, S. and S. Clerides, “ Integrating and Assessing Economic
Evidence under Cyprus Competition Law: Case Comment on the
Cyprus Commission for the Protection of Competition Decision No.
42/2014”, December 2016.
07-16
Zachariadis, T., “Proposal for a Green Tax Reform in Cyprus”,
December 2016.
06-16
Savva, C., “Factors Affecting Housing Prices: International Evidence”,
November 2016.
05-16
Papamichael, C. and N. Pashourtidou “The role of survey data in the
construction of short-term GDP growth forecasts”, September 2016.
04-16
Karagiannakis, C., P. Pashardes, N. Pashourtidou and S. Andreou
“The CypERC property price index: data and estimation methods”,
May 2016.
03-16
Michail A. M. and M.C. Polemidiotis “ Estimates of Public, Housing
and Other Private Sectors Net Capital Stocks for the Cyprus
Economy: 1995Q1-2015Q4”, April 2016.
02-16
Polycarpou, A. “The output gap in Cyprus and EU-28”, April 2016,
01-16
Koutsampelas, C. “The Cypriot GMI scheme and comparisons with
other European countries”, April 2016.
10-15
Polycarpou, A. “Methodologies for estimating the output GAP with an
application to Cyprus”, December 2015.
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