Main data files comprise 22 variables in three subcategories of risk (political, financial, and economic) for 146 countries for 1984-2021. Data are annual averages of the components of the ICRG Risk Ratings (Tables 3B, 4B, and 5B) published in the International Country Risk Guide. Indices include: political: government stability, socioeconomic conditions, investment profile, internal conflict, external conflict, corruption, military in politics, religion in politics, law and order, ethnic tensions, democratic accountability, and bureaucratic quality; financial: foreign debt, exchange rate stability, debt service, current account, international liquidity; and economic: inflation, GDP per head, GDP growth, budget balance, current account as % of GDP. Table 2B provides annual averages of the composite risk rating. Table 3Ba provides historical political risk subcomponents on a monthly basis from May 2001-February 2022. Also includes the IRIS-3 dataset by Steve Knack and Philip Keefer, which covers the period of 1982-1997 and computed scores for six additional political risk variables: corruption in government, rule of law, bureaucratic quality, ethnic tensions, repudiation of contracts by government, and risk of expropriation. Additional data files provide country risk ratings and databanks (economic and social indicators) for new emerging markets for 2000-2009.

The Researcher Datasets from the PRS Group provide annual and monthly weighted average risks across countries from 1984 on a wealth of Political, Economic and Financial risk topics for 140 monitored countries. The Composite risk index is based on a possible 100 points and aggregates political, financial and economic risk using the PRS Composite Risk Rating formula.

The Researcher Datasets from the PRS Group provide annual and monthly weighted average risks across countries from 1984 on a wealth of Political, Economic and Financial risk topics for 140 monitored countries. The components of the ICRG Financial Risk Rating are Foreign Debt as a % of GDP, Exchange Rate Stability, Debt Service as a % of Exports of Goods & Services (XGS), Current Account as a % of Exports of Goods and Services, and International Liquidity.

The International Country Risk Guide (ICRG) produced by The PRS Group is a commercial source of country risk analysis and ratings. The Researcher's Datasets cover all 140 ICRG countries and include average ICRG political, economic, financial, and composite risk components from 1984 to the present. UBC provides access to two Researcher's Dataset tables with data from 1984 to the present: ICRG Table 2B. Annual averages of the composite risk rating, an element of the ICRG's Table 2B. ICRG's composite risk scores aggregates the political, financial, and economic ratings for each country's overall risk. ICRG Table 3B. Annual averages for each of the 12 components for Political Risk. Table 3B has risk ratings for: Bureaucracy quality Corruption Law and order Government stability Socioeconomic conditions Investment profile Internal conflict External conflict Military in politics Religious tensions Ethnic tensions Democratic accountability

The Researcher Datasets from the PRS Group provide annual and monthly weighted average risks across countries from 1984 on a wealth of Political, Economic and Financial risk topics for 140 monitored countries. The components of the ICRG Economic Risk Rating are GDP per Head, Real GDP Growth, Annual Inflation Rate, Budget Balance as a Percentage of GDP and Current Account as a % of GDP.

The Researcher Datasets from the PRS Group provide annual and monthly weighted average risks across countries from 1984 on a wealth of Political, Economic and Financial risk topics for 140 monitored countries. The components of the ICRG Political Risk Rating are Bureaucracy Quality, Corruption, Investment Profile, Government Stability, Socioeconomic Conditions, Internal Conflict, External Conflict, Military in Politics, Religious Tensions, Law and Order, Ethnic Tensions, and Democratic Accountability.

The PRS Group's International Country Risk Guide provides annual risk ratings for 140 countries.

This dataset is used for paper "Impact of the political risk on food reserve ratio: evidence across countries". We explore how the political risk impacts on food reserve ratio using an unbalanced panel data covering 75 countries from1991 to 2019. This dataset includes International Country Risk Guide ratings (ICRG) database, FAOSTAT database, Production, Supply, and Distribution (PSD) online database, Emergency Events Database (EM-DAT), and World Bank Open (WBO) database.

Informatization index system.

Descriptive statistical results of the variables.

The impact of different types of CRs on TR.

The impact of different types of CRs on TE.

The basic econometric model for the suggested interaction effect of resource endowments and institutional quality on economic growth is borrowed from Boschini et al., 2007 and Brunnschweiler, 2007. The approximation for institutional quality must be carefully chosen. The standard proxy variables that are typically employed in the literature with respect to the resource curse are indices such as ICRG, BERI, BI ratings (pioneered by Knack and Keefer, 1995; Mauro, 1995), and the Worldwide Governance Indicators (WGI) suggested by Kaufmann et al. (2010). However, a potential bias in these indicators may arise from the fact that they are based on the subjective assessments of respondents. For instance, the evaluators may be more likely report that governance in a country is good during times of strong economic performance. The use of CIM also has potential risks if the measure is idiosyncratic and irrelevant to contract enforcement and property rights. Clague et al. (1999) reviewed case studies from several countries and found that CIM is a good measure of institutional quality, though some country examples demonstrate idiosyncratic cases. We also use the indicators of governance used by Kaufmann et al. (2010) such as Voice and Accountability (VA), Political Stability and the Absence of Violence (PA), Government Effectiveness (GE), Regulatory Quality (RQ), Rule of Law (RL), and Control of Corruption (CC)—with CIM, was illustrated to examine the suitability of CIM as an institutional quality variable. Purpose: The data obtained is employed for investigation of dissertation. My main objective in this analysis was to assess the impact of resource rent shares of income per capita through various resource curse channels. I hypothesized that natural resource abundance only encourages economic development in countries with high quality economic institutions.

Captures full set of data compiled from sources including IMF Article IV Country Reports, Energy Information Administration, World Development Indicators and the International Country Risk Group (ICRG).

Panel cointegration test.

The impact of CR on tourism in different regions.

The impact of CR on tourism in countries with different income levels.

The moderating effects of informatization.

Notes: Dependent variable: real GDP per capita in logarithm.Cross-country panel data consisting of annual spanning 1980–2008.Estimation method: Dynamic GMM estimator Arellano and Bond (1991).A full set of year dummies is included to control for common time effects. The full regressions includes lagged of GDP per capita, government consumption, consumer price index, secondary school enrolment, gross capital formation, Liquid liability and ICRG.Numbers below coefficients are the t-statistic.***, **, *denotes statistical significance at the 1%, 5% and 10% levels, respectively.