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Public policy reforms and their impact on productivity, investment and employment: new evidence from OECD and non-OECD countries
Balázs Égert
Balázs Égert
Affiliation: OECD Economics Department, Paris, France; CESifo Munich Poschingerstrasse 5, Muenchen, Germany; EconomiX at the University of Paris X Nanterre, Nanterre, France
0000-0002-9540-4205
Correspondence
Balazs.Egert@oecd.org
Article | Year: 2022 | Pages: 179 - 205 | Volume: 46 | Issue: 2 Received: June 1, 2021 | Accepted: February 7, 2022 | Published online: June 1, 2022
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FULL ARTICLE
FIGURES & DATA
REFERENCES
CROSSMARK POLICY
METRICS
LICENCING
PDF
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Source
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Country coverage
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Time coverage
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Product market regulation
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Overall
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OECD Product market regulation Indicators database
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Around 60
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Every five years, only one observation for about 15 countries
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Barriers to entry
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Barriers to trade & investment
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Scope of state control
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General business sector regulation
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Business regulation
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Fraser Institute
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More than 100 countries
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Annual, about 10 years
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Cost of contract enforcement
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World Bank Doing Business Indicators
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More than 100 countries
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Annual, about 10 years
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Time of contract enforcement
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Cost of insolvency procedures
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Time of insolvency procedures
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Cost of starting a business
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Time of starting a business
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Labour market regulation
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EPL regular contracts
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OECD
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Around 60 countries, 10 countries different than for PMR
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Annual, 30 years, only one observation for about 15 countries
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Labour market regulation
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Fraser Institute
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More than 100 countries
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Annual, about 10 years
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EPL regular contracts
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Cambridge
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117 countries
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Annual, 40 years
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Institutions
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Legal system
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Fraser Institute
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Around 100 countries
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Annual, about 10 years
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Legal system – enforcement
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Legal system – judicial independence
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Rule of law
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WB's World Governance Indicators
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Around 100 countries
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Political stability
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Corruption
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Government effectiveness
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Financial development
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Financial liberalisation – EFW
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Fraser Institute
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Around 100 countries
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Annual, until 2005
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Domestic credit % GDP
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World Bank's World Development Indicators database
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Around 100 countries
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Annual, about 30 years
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Domestic private credit % GDP
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Bank branches per capita
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Stock market capitalisation % GDP
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Stock market turnover % GDP
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Trade openness
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Openness
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World Bank's World Development Indicators database
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Around 100 countries
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Annual, about 30 years
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Log openness
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Log openness – size adjusted
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Own calculation based on WDI
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Trade liberalisation – EFW
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Fraser Institute
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Around 100 countries
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Annual, until 2005
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Innovation intensity
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R&D spending % GDP
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World Bank's World Development Indicators database
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Around 100 countries
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Annual, about 30 years
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Patents/capita
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Source: Author.
Note: LCAP, on the vertical axis, denotes log per capita income (USD, constant PPP). On the horizontal axes are displayed the policies and institutions. For the rule of law, corruption and government effectiveness, higher numbers show a stronger rule of law, less corruption and a more effective government. START_COST, CONTRACT_COST and INSOLV_COST refer to the cost of starting a business, the time required for contract enforcement and insolvency procedures. REG_BUS and REG_LM_EFW are the EFW’s business regulation and labour market regulation indicators: higher values indicate more business-friendly regulation. EPL_CBR is the Cambridge Labour Regulation Indicator relating to regular contract: higher numbers indicate more stringent regulation.Source: Author.
Note: A_LCAP, on the vertical axis, denotes log per capita income (USD, constant PPP, country averages). On the horizontal axes are displayed the policies and institutions. For the rule of law, corruption and government effectiveness, higher numbers show a stronger rule of low, less corruption and a more effective government. For the OECD’s PMR indicator, its sub-components and the OECD and Cambridge EPL indicators, higher figures reflect more stringent regulation. For the EFW’s labour market regulation indicator, higher values indicate less stringent regulation. Source: Author
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MFP
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Capital deepening
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Employment rate
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Per capita income
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Linear relationships
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Within dimension
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Institutions
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Yes
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No
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Yes
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Yes
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Business regulation
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Yes
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No
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No
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No
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Product market regulation
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–
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–
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–
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–
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Labour market regulation
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–
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Yes
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Yes
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–
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Financial system development
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Yes
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No
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–
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Yes
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Between dimension
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Institutions
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Yes
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No
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Yes
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Yes
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Business regulation
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?
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No
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No
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No
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Product market regulation
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BTI
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BTE, SSC
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BTE, SSC
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BTI
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Labour market regulation
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Yes??
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No
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Yes??
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No
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Financial system development
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Yes
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Yes
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–
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Yes
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Non-linear relationships
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conditional on
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per capita income
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Business regulation
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Yes
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No
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Yes
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Yes
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Product market regulation
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BTE,BTI,SSC
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NO
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BTE, SSC
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BTE,BTI,SSC
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Labour market regulation
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No
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No
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Yes
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No
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institutions
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Business regulation
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Yes
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No
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Yes
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Yes
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Product market regulation
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BTE,BTI,SSC
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BTE, SSC
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BTE, SSC
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BTE,BTI,SSC
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Labour market regulation
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No
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No
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Yes
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No
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labour market regulations
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Business regulation
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No
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No
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No
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No
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Product market regulation
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BTE,BTI,SSC
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NO
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BTE,SSC
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BTE,BTI,SSC
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Labour market regulation
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No
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No
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No
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No
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Notes: Results on the linear relationship are split into two main parts: within dimension (coefficient estimates identified from the time variation in the data); and between dimension (coefficient estimates obtained on cross-sectional data). Non-linear relationships are estimated only on cross-section data (because no time series are available for PMR). The column ‘non-linear variables’ lists the variables, which take different coefficients, depending on the level of other variables. These ‘other variables’ are named in the rows “conditional on …” and are per capita income, institutions and labour market regulations. ‘YES’ implies a statistically significant relationship. ‘?’ implies that the estimated relationship is not very robust. ‘NO’ indicates the absence of a statistically significant relationship. ‘--’ indicates that the variable could not be included in the regressions. BTE, BTI and SSC indicate that there is a statistically significant relationship between the PMR sub-components barriers to entry (BTE), barriers to trade and investment (BTI) and the scope of state control (SSC) on the one hand and economic outcomes (MFP, capital deepening, the employment rate and per capita income) on the other hand.
Note: The ratio displayed above is the ratio between the standard deviation calculated on crosssection observations (averages for individual countries, the pure between effect) and the standard deviation of the series stripped of country means and common time trends (pure within effect). Source: Author’s calculations.
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Impact through
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Total impact
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MFP
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K/Y
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L
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Per capita income: aggregated from MFP,
K/Y and L
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Policy measured as one standard
deviation
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Within
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Between
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Within
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Between
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Within
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Between
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Within
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Between
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Institutions
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Government effectiveness
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7.4
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50.0
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0.8
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5.2
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8.2
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55.2
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Rule of law
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5.0
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42.9
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0.5
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4.5
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5.5
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47.4
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Political stability
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5.7
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24.0
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1.0
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4.3
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6.7
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28.3
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Corruption
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5.9
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39.8
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0.9
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6.0
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6.8
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45.8
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Business regulation
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Cost of starting a business
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0.8
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1.3
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9.0
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15.6
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9.8
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16.9
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Cost of contract enforcement
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1.4
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13.5
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1.4
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13.5
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Time of insolvency procedures
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5.6
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14.6
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1.1
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2.8
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6.6
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17.4
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Product market regulation
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PMR – overall
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–
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–
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8.9
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–
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1.5
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–
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10.4
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PMR – barriers to entry
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–
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17.3
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–
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5.2
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–
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2.0
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–
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24.5
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PMR – barriers to trade & investment
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–
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8.3
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–
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–
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–
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8.3
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PMR – scope of state control
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–
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–
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6.4
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–
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4.1
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–
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10.5
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Labour market regulation
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EPL – OECD regular contracts
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0.9
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0.9
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EPL – Cambridge indicator
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0.8
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3.1
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0.8
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3.1
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Labour market regulation (EFW)
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2.1
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5.5
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0.8
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2.0
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2.9
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7.5
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Financial development
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Banking sector
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4.9
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12.4
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4.2
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10.7
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9.1
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23.0
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Financial markets
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8.1
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17.2
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8.1
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17.2
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Note: MFP, K/Y and L indicate by how much per capita income would increase due to policy changes affecting the three supply-side channels. The change in the indicators is defined as one standard deviation in the data. Columns named ‘within’ show that the change in the policies are based on the within dimension (variation over time). Columns named ‘between’ show that the changes in the policies are obtained from the between (cross-section) dimension. The effects are calculated following the methodology set out in box 1 in Égert and Gal (2016). Empty cells indicate the absence of robust empirical relationships. Cells filled with “--“ indicate that regression analysis was not possible for the particular variable and dimension (PMR indicator over time). The coefficient estimates used to calculate the effect are the average of the minimum and maximum coefficient estimates. Table C11 summarises from which particular regressions the coefficient estimates are used. Source: Author’s calculations.
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If per
capita income is
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If rule of
law is
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If OECD's
EPL on regular contracts is
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Below
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Above
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Below
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Above
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Below
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Above
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The estimated
threshold
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The estimated
threshold
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The estimated
threshold
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Effects on MFP of
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PMR – overall
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40.4
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17.4
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28.2
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12.6
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30.4
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25.3
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PMR – barriers to entry
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24.5
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1.5
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19.4
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2.8
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19.4
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13.0
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PMR – barriers to trade & investment
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53.1
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15.8
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35.5
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11.0
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27.7
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41.0
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PMR – scope of state controll
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27.1
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5.3
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18.1
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2.8
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16.9
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11.0
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Note: Numbers in bold indicate that the calculations are based on coefficient estimates that were statistically not significant at the conventional level of 10%. Source: Author’s calculations
Variables
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Min
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Max
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Mean
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St. dev.
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Worldwide sample
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Per capita income
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5.29
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11.62
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8.75
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1.31
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Openness
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0.31
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449.99
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91.94
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51.78
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Log Openness
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-1.18
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6.11
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4.40
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0.52
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Log Openness (size adjusted)
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-4.93
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1.99
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0.24
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0.49
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R&D spending %GDP
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0.01
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4.52
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1.00
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0.99
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Rule of law
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-2.67
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2.00
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0.00
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0.99
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Cost of starting a business
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0.00
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1,540.00
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67.00
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143.00
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Time of starting a business
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1.00
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687.00
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41.00
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59.00
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Labour market regulation – EFW
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2.34
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9.73
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11475.00
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1.49
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Business regulation – EFW
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2.86
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8.89
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6.01
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1.04
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Finance – bank branches per capita
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0.13
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237.07
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19.38
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23.96
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Stock market capitalisation % GDP
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0.04
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606.00
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54.91
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62.54
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OECD sample
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Openness
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5.73
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371.44
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68.15
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43.87
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Log Openness
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1.75
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5.92
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4.04
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0.61
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Log Openness (size adjusted)
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-2.12
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1.32
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0.03
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0.49
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Business spending on R&D % GDP – OECD
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0.01
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3.76
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1.05
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0.73
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General spending on R&D % GDP – OECD
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0.15
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4.48
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1.68
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0.88
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General spending on basic R&D % GDP – OECD
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0.05
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0.90
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0.31
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0.16
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ETCR – overall
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0.79
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6.00
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4.08
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1.47
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ETCR – entry barriers
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0.43
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6.00
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3.77
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1.84
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ETCR – public ownership
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0.83
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6.00
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4.29
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1.43
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EPL regular contracts
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0.26
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5.00
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2.18
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0.83
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ALMP spending
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0.45
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22.00
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22.00
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21.53
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Variables
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Worldwide sample
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OECD sample
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Min
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Max
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Mean
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St. dev.
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Min
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Max
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Mean
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St. dev.
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Institutions
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Legal system
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2.23
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8.93
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5.53
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1.61
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4.86
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8.54
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7,27
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1,07
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Legal system – enforcement
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0.00
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8.11
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4.46
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1.75
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3.22
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8.11
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5,75
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1,29
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Legal system – judicial independence
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0.60
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9.15
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4.80
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2.15
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3.85
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9.17
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7,06
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1,74
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Rule of law
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-2.38
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1.94
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0.01
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0.99
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-0.53
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1.94
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1,27
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0,60
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Civil liberties
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1.00
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7.00
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4.78
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1.81
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4.02
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7.00
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6,29
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0,86
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Polity2 – political stability
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-10.00
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10.00
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3.78
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6.17
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27.00
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10.00
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8,01
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3,17
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Corruption
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-1.71
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2.45
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0.01
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0.98
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-0.31
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2.44
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1,33
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0,80
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Government effectiveness
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-2.18
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2.18
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0.00
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0.99
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0.16
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2.14
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1,36
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0,56
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Business
environment
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Cost of contract enforcement
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8.00
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163.00
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35.00
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26.00
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8.00
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39.00
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21,00
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8,00
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Time of contract enforcement
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133.00
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1,715.00
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628.00
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305.00
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216.00
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1,332.00
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517,00
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260,00
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Cost of insolvency procedures
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1
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76.00
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17.00
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12
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1.00
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23.00
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10,00
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6,00
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Time of insolvency procedures
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0.40
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6.97
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2.75
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1.21
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0.40
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5.84
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1,92
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1,16
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Cost of starting a business
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0.00
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991.49
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66.32
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121.4
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0.05
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20.69
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6,80
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6,42
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Time of starting a business
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2.78
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690.71
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41.86
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60.34
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2.71
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61.08
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16,83
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11,68
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OECD Product Market Regulation Indicator
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PMR – overall
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|
|
|
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1.18
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2.8
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1,73
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0,35
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PMR – barriers to entry
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|
|
|
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1.49
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3.07
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2,06
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0,37
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PMR – barriers to trade & investment
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|
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|
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0.20
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2.09
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0,74
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0,41
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PMR – scope of state control
|
|
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1.51
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3.92
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2,41
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0,54
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|
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June, 2022 II/2022 |