Data of ten countries: seven countries are classified as ‘developing’ – Bolivia, Cambodia, Ecuador, Kazakhstan, Morocco, Nepal and Tanzania, while three countries – Hungary, Slovenia and USA are designated as ‘developed.’ These countries have the complete HDI and tourist arrivals’ data for the period 1996 – 2019. The study analyses the impact of tourism to human development in ten countries, that also include other variables: jobs, government effectiveness and political stability, using three different panel estimation techniques: random, fixed effect and Least-squares Dummy variables (LSDV).

Data sourced from the World Governance Indicators (WGI), World Development Indicators (WDI), Human Development Index (HDI), and Inequality measured by the Palma Ratio. This dataset includes six governance indicators from WGI, human development metrics from HDI, economic growth statistics, electricity supply data, CO2 emissions and inequality indicators. The comprehensive dataset spans from 2003 to 2018 and encompasses between 36 to 106 countries, depending on the specific variables.

This dataset includes annual panel data for 43 countries from 1990 to 2021. It contains variables on primary energy consumption, Human Development Index (HDI), carbon dioxide (CO₂) emissions, foreign direct investment (FDI), and population. The data were compiled from publicly available sources.

Linear regression (multivariable) of total recoveries per million and predictor variables.

The file contains data on a set of variables linked to human development, corruption, democracy, economic freedom, investment, and social spending, for a sample of 135 developed and developing countries during the period 2005-2021.

Linear regression (multivariable) of total cases per million and predictor variables.

The data collected aim to test whether English proficiency levels in a country are positively associated with higher democratic values in that country. English proficiency is sourced from statistics by Education First’s "EF English Proficiency Index" which covers countries' scores for the calendar year 2022 and 2021. The EF English Proficiency Index ranks 111 countries in five different categories based on their English proficiency scores that were calculated from the test results of 2.1 million adults. While democratic values are operationalized through the liberal democracy index from the V-Dem Institute annual report for 2022 and 2021. Additionally, the data is utilized to test whether English language media consumption acts as a mediating variable between English proficiency and democracy levels in a country, while also looking at other possible regression variables. In order to conduct the linear regression analyses for the dats, the software that was utilized for this research was Microsoft Excel.The raw data set consists of 90 nation states in two years from 2022 and 2021. The raw data is utilized for two separate data sets the first of which is democracy indicators which has the regression variables of EPI, HDI, and GDP. For this table set there is a total of 360 data entries. HDI scores are a statistical summary measure that is developed by the United Nations Development Programme (UNDP) which measures the levels of human development in 190 countries. The data for nominal gross domestic product scores (GDP) are sourced from the World Bank. Having strong regression variables that have been proven to have a positive link with democracy in the data analysis such as GDP and HDI, would allow the regression analysis to identify whether there is a true relationship between English proficiency and democracy levels in a country. While the second data set has a total of 720 data entries and aims to identify English proficiency indicators the data set has 7 various regression variables which include, LDI scores, Years of Mandatory English Education, Heads of States Publicly speaking English, GDP PPP (2021USD), Common Wealth, BBC web traffic and CNN web traffic. The data for years of mandatory English education is sourced from research at the University of Winnipeg and is coded in the data set based on the number of years a country has English as a mandatory subject. The range of this data is from 0 to 13 years of English being mandatory. It is important to note that this data only concerns public schools and does not extend to the private school systems in each country. The data for heads of state publicly speaking English was done through a video data analysis of all heads of state. The data was only used for heads of state who had been in their position for at least a year to ensure the accuracy of the data collected; with a year in power, for heads of state that had not been in their position for a year, data was taken from the previous head of state. This data only takes into account speeches and interviews that were conducted during their incumbency. The data for each country’s GDP PPP scores are sourced from the World Bank, which was last updated for a majority of the countries in 2021 and is tied to the US dollar. Data for the commonwealth will only include members of the commonwealth that have been historically colonized by the United Kingdom. Any country that falls under that category will be coded as 1 and any country that does not will be coded as 0. For BBC and CNN web traffic that data is sourced by using tools in Semrush which provide a rough estimate of how much web traffic each news site generates in each country. Which will be utilized to identify the average number of web traffic for BBC News and CNN World News for both the 2021 and 2022 calendar. The traffic for each country will also be measured per capita, per 10 thousand people to ensure that the population density of a country does not influence the results. The population of each country for both 2021 and 2022 is sourced from the United Nations revision of World Population Prospects of both 2021 and 2022 respectively.

The Human Development Index (HDI) was developed by the United Nations Development Programme (UNDP) in the Human Development Report 1990 to measure the level of economic and social development of the United Nations member countries. The HDI is a composite indicator based on three basic variables: life expectancy, educational attainment and quality of life, and is calculated according to a certain methodology. "The One Belt One Road (OBOR) human development resilience dataset is a comprehensive indicator of human development resilience in each country. "The human development resilience dataset for countries along the Belt and Road is a comprehensive diagnosis based on sensitivity and adaptability analysis using year-by-year data of the Human Development Index for countries along the Belt and Road from 2000 to 2020. The Human Development Resilience Indicator (HDRI) data was prepared based on sensitivity and adaptation analysis. Please refer to the documentation for the methodology of preparing the dataset. "The Human Development Resilience Dataset for countries along the Belt and Road is an important reference for analysing and comparing the current state of human development resilience in each country.

Spearman’s rank-order correlations between variables.

Users are recommended to consult the author (malcolm.mistry@unive.it / malmistry1977@gmail.com) for an updated version which includes more recent years.The human discomfort indices (HDIs) are computed using meteorological parameters from the Global Land Data Acquisation System (GLDAS) ver. 2 (@ 0.25 degree global gridded resolution). The dataset referred to as "HDI_0p25_1970_2018" covers 49 years over the period 1970-2018. Following HDIs are included:(i) Apparent Temperature (AT) indoors: Deg Celsius(ii) AT outdoors in shade, as defined by Australian Bureau of Meteorology (ABM) and National Oceanic and Atmospheric Administration (NOAA): Deg Celsius(iii) Discomfort Index (DI): Unitless(iv) Humidex (HDEX): Unitless(v) Heat Index (HI): Deg Celsius(vi) Wet Bulb Globe Temperature (WBGT), as defined by ABM and by Gagge and Nishi (1976): Unitless(vii) Wet Bulb Temperature (WBT): Deg Celsius(viii) Windchill Temperature (WCT): Deg CelsiusHDIs on daily timesteps covering years 1970-2018 are available as individual (annual) NetCDF-4 (.nc4) files. The files follow the naming convention 'gldas_HDI_daily_year.nc4'; wherein "HDI" is the abbreviation of the index (AT_indoors, AT_outdoor_shade_ABM, AT_out_shade_NOAA, DI, humidex, HI, wbgt_ABM, wbgt, wet_bulb or windchill_T), and "year" the time period over which the HDI are computed on daily timesteps. Some of the indices use two methodologies for computation as defined in literature (e.g. ABM, NOAA). These abbreviations are also included in the filenames and the details (units, attributes etc) can be checked using 'ncdump -h filename.nc4'.In addition to individual HDI, the associated meteorological variables (referred to 'secondary variables') used to compile the HDIs are available upon request from the author. These variables (all on daily timesteps for the same period 1970-2018) include vapor pressure (vp), saturation vapor pressure (svp), vapor pressure deficit (vpd), relative humidity (rh). 'vpd' is actually not used in the computation of any of the HDI, but generated as an add-on variable using 'rh' and 'svp'.Grid-cells with missing values are identified by "1.e+20f".Important: GLDAS ver-2 comprises of two sub-versions (ver. 2.0 for period 1970-2010 and ver 2.1 for period 2000-present day). The HDIs computed using the input variables may show a break in time-series at a few locations around the years 2010-11. Users are therefore advised caution when using the data for trend analysis for instance. Further details on the merging of the two versions can be found below:https://disc.gsfc.nasa.gov/information/faqs?title=Should%20I%20use%20GLDAS%20Version%202.0%20(GLDAS-2.0)%20or%20GLDAS%20Version%202.1%20(GLDAS-2.1)%3F

Linear regression (multivariable) of total cases of deaths per million and predictor variables.

This dataset enables studying the relationship between a country's economic and social factors — such as GDP per capita, government health expenditure, Human Development Index (HDI), World Happiness Index, and density of doctors per population — with several key health indicators, like alcohol consumption, life expectancy, child mortality, non-communicable disease mortality, obesity prevalence, and undernourishment rates. It covers 50 countries from 2002 to 2021.A dashboard is also provided to facilitate the study, including plots for comparison of any selected variables for any of the available years, countries and geographic regions.

This dataset and dashboard has been created as part of a data management project for university IQS, Ramon Llull.

Contents of the dataset on country/macro level includes nine variables considering school and education system characteristics as well as country characteristics: number of school types/tracks for 9th grade/15-year-olds; age at first selection; preschool obligation; compulsory school years/education years (with pre-primary school); government expenditure on education, total (% of GDP); mean years of schooling; Human Development Index (HDI); Gender Inequality Index (GII); women’s share of seats in parliament (in %)

The data set contains information on 82 countries and regions that participated in the PISA study. Most of the data are for the school year period of 2017/18, however older and newer data is used as well if other sources were not available. The documents used to create the dataset (including European Commisssion, OECD, education ministries) can be found in the reference list in the excel file and can be requested from the author.

The aim of this study was to evaluate the performance of the Centers for Dental Specialties (CDS) in the country and associations with sociodemographic indicators of the municipalities, structural variables of services and primary health care organization in the years 2004-2009. The study used secondary data from procedures performed in the CDS to the specialties of periodontics, endodontics, surgery and primary care. Bivariate analysis by χ2 test was used to test the association between the dependent variable (performance of the CDS) with the independents. Then, Poisson regression analysis was performed. With regard to the overall achievement of targets, it was observed that the majority of CDS (69.25%) performance was considered poor/regular. The independent factors associated with poor/regular performance of CDS were: municipalities belonging to the Northeast, South and Southeast regions, with lower Human Development Index (HDI), lower population density, and reduced time to deployment. HDI and population density are important for the performance of the CDS in Brazil. Similarly, the peculiarities related to less populated areas as well as regional location and time of service implementation CDS should be taken into account in the planning of these services.

This map is adapted from the outstanding work of Dr. Joseph Kerski at ESRI. A map of political, social, and economic indicators for 2010. Created at the Data Analysis and Social Inquiry Lab at Grinnell College by Megan Schlabaugh, April Chen, and Adam Lauretig.Data from Freedom House, the Center for Systemic Peace, and the World Bank.Shapefile:Weidmann, Nils B., Doreen Kuse, and Kristian Skrede Gleditsch. 2010. The Geography of the International System: The CShapes Dataset. International Interactions 36 (1).Field Descriptions:

Variable Name Variable Description Years Available Further Description Source

TotPop Total Population 2011 Population of the country/region World Bank

GDPpcap GDP per capita (current USD) 2011 A measure of the total output of a country that takes the gross domestic product (GDP) and divides it by the number of people in the country. The per capita GDP is especially useful when comparing one country to another because it shows the relative performance of the countries. World Bank

GDPpcapPPP GDP per capita based on purchasing power parity (PPP) 2011

World Bank

HDI Human Development Index (HDI) 2011 A tool developed by the United Nations to measure and rank countries' levels of social and economic development based on four criteria: Life expectancy at birth, mean years of schooling, expected years of schooling and gross national income per capita. The HDI makes it possible to track changes in development levels over time and to compare development levels in different countries. World Bank

LifeExpct Life expectancy at birth 2011 The probable number of years a person will live after a given age, as determined by mortality in a specific geographic area. World Bank

MyrSchool Mean years of schooling 2011 Years that a 25-year-old person or older has spent in schools World Bank

ExpctSch Expected years of schooling 2011 Number of years of schooling that a child of school entrance age can expect to receive if prevailing patterns of age-specific enrolment rates persist throughout the child’s life. World Bank

GNIpcap Gross National Income (GNI) per capita 2011 Gross national income (GNI) is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. GNI per capita is gross national income divided by mid-year population. World Bank

GNIpcapHDI GNI per capita rank minus HDI rank 2011

World Bank

NaIncHDI Nonincome HDI
2011

World Bank

15+LitRate Adult (15+) literacy rate (%). Total 2010

UNESCO

EmplyAgr Employment in Agriculture 2009

World Bank

GDPenergy GDP per unit of energy use 2010 The PPP GDP per kilogram of oil equivalent of energy use. World Bank

GDPgrowth GDP growth (annual %) 2011

World Bank

GDP GDP (current USD) 2011

World Bank

ExptGDP Exports of Goods and Service (% GDP) 2011 The value of all goods and other market services provided to the rest of the world World Bank

ImprtGDP Imports of Goods and Service (% GDP) 2011 The value of all goods and other market services received from the rest of the world. World Bank

AgrGDP Agriculture, Value added (% GDP) 2011 Agriculture corresponds to ISIC divisions 1-5 and includes forestry, hunting, and fishing, as well as cultivation of crops and livestock production. Value added is the net output of a sector after adding up all outputs and subtracting intermediate inputs. World Bank

FDI Foreign Direct Investment, net (current USD) 2011 Foreign direct investment are the net inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor. It is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in the balance of payments. World Bank

GNIpcap GNI per capita PP 2011 GNI per capita based on purchasing power parity (PPP). PPP GNI is gross national income (GNI) converted to international dollars using purchasing power parity rates. An international dollar has the same purchasing power over GNI as a U.S. dollar has in the United States. GNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. World Bank

Inflatn Inflation, Consumer Prices (annual %) 2011 Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. World Bank

InfltnGDP Inflation, GDP deflator (annual %) 2011 Inflation as measured by the annual growth rate of the GDP implicit deflator shows the rate of price change in the economy as a whole. The GDP implicit deflator is the ratio of GDP in current local currency to GDP in constant local currency. World Bank

PctWomParl % women in national parliament 2010

United Nations

IntnetUser Internet Users, per 100 peple 2011 Internet users are people with access to the worldwide network. World Bank

HIVPrevlnc Estimated HIV Prevalence% - (Ages 15-49) 2009 Prevalence of HIV refers to the percentage of people ages 15-49 who are infected with HIV. UNAIDS estimates. UNAIDS

AgrLand Agricultural land (% of land area) 2009 Agricultural land refers to the share of land area that is arable, under permanent crops, and under permanent pastures. World Bank

AidRecPP Aid received per person (current US$) 2010 Net official development assistance (ODA) per capita consists of disbursements of loans made on concessional terms (net of repayments of principal) and grants by official agencies of the members of the Development Assistance Committee (DAC), by multilateral institutions, and by non-DAC countries to promote economic development and welfare in countries and territories in the DAC list of ODA recipients; and is calculated by dividing net ODA received by the midyear population estimate. It includes loans with a grant element of at least 25 percent (calculated at a rate of discount of 10 percent). World Bank

AlcohAdul Alcohol consumption per adult (15+) in litres 2008 Liters of pure alcohol, computed as the sum of alcohol production and imports, less alcohol exports, divided by the adult population (aged 15 years and older). World Health Organization

ArmyPct Military expenditure (% of central government expenditure) 2008 Military expenditures data from SIPRI are derived from the NATO definition, which includes all current and capital expenditures on the armed forces, including peacekeeping forces; defense ministries and other government agencies engaged in defense projects; paramilitary forces, if these are judged to be trained and equipped for military operations; and military space activities. Such expenditures include military and civil personnel, including retirement pensions of military personnel and social services for personnel; operation and maintenance; procurement; military research and development; and military aid (in the military expenditures of the donor country). World Development Indicators (World Bank)

TFR Total Fertility Rate 2011 The average number of children that would be born per woman if all women lived to the end of their childbearing years and bore children according to a given fertility rate at each age. This indicator shows the potential for population change in a country. World Bank

CO2perUSD CO2 kg per USD 2008 Carbon dioxide emissions are those stemming from the burning of fossil fuels and the manufacture of cement. They include carbon dioxide produced during consumption of solid, liquid, and gas fuels and gas flaring. World Bank

ExpdtrPrim Expenditure per student, primary (% of GDP per capita) 2008 Public expenditure per pupil as a % of GDP per capita. Primary is the total public expenditure per student in primary education as a percentage of GDP per capita. Public expenditure (current and capital) includes government spending on educational institutions (both public and private), education administration as well as subsidies for private entities (students/households and other privates entities). World Bank

ExpdtrSecd Expenditure per student, secondary (% of GDP per capita) 2008 Public expenditure per pupil as a % of GDP per capita. Secondary is the total public expenditure per student in secondary education as a percentage of GDP per capita. World Bank

ExpdtrTert Expenditure per student, tertiary (% of GDP per capita) 2008 Public expenditure per pupil as a % of GDP per capita. Tertiary is the total public expenditure per student in tertiary education as a percentage of GDP per capita. World Bank

FDIoutf Foreign direct investment, net outflows (% of GDP) 2010 Foreign direct investment are the net inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor. It is the sum of equity capital, reinvestment of earnings, other long-term capital, and short-term capital as shown in the balance of payments. This series shows net outflows of investment from the

This data harmonizes waves 2, 4, and 5 from the European Social Survey, waves 5 and 6 from the World Values Survey, and wave 4 from the European Values Study. The aim of the study was to analyze gender attitudes using the statement "Men should have more right to a job than women when jobs are scarce". For information on those people who stayed in the sending countries data from WVS6 for the following countries was chosen: Algeria, Argentina, Australia, Brazil, Chile, China, Colombia, Cyprus, Ecuador, Estonia, Ghana, Hong Kong, India, Iraq, Japan, Kazakhstan, Kyrgyzstan, Lebanon, Mexico, Morocco, Nigeria, Pakistan, Peru, Philippines, Poland, Romania, Russia, Rwanda, Singapore, South Africa, South Korea, Thailand, Tunisia, Turkey, Ukraine, the United States, Uruguay, and Zimbabwe.

I also employ data for several countries from Wave 5 for those societies that were not covered during the last wave: Bulgaria, Canada, Egypt, Finland, Hungary, Indonesia, Italy, Iran, Moldova, Norway, Vietnam, Serbia and Montenegro, and Zambia.

I add European societies that have not been covered by the WVS by using the European Values Study 2008: Albania, Austria, Bosnia and Herzegovina, Croatia, Czech Republic, Denmark, Greece, Ireland, Lithuania, Luxembourg, Macedonia, Slovak Republic, and Slovenia. This gives 65 sending societies in total. As people could have migrated from the European countries of the main focus, namely, Belgium, Germany, France, the Netherlands, Portugal, Spain, Sweden, Switzerland, and the UK, I add those as well, with a final total of 73 sending countries.

Such variables as age, gender, migration status, religiosity measured by self-attribution (How religious are you?), Importance of God, and church attendance as well as denomination are added. Education is binarized for higher o higher. Employment is measured by 6 categories, marital status - by 5 categories. Those who refused to answer were coded into a separate category "refused".

Country-level variables: Human Development Index (HDI), GDP per capita, Polity IV, Freedom House Civil Liberties Index, Gender Inequality Index (by UNDP), unemployment ratio of women to men; percentage of women in the labor market, percentage of women in parliaments, percentage of Islamic population in the country, Islamic majority in the country (binary), level of religiosity in the country (country average for ``How important is God in your life?"), post-communism, Cultural zones from Inglehart's cultural map (8 groups).

a15+ = person aged 15 or older.b2012–2014 = three years average.cDES = Dietary Energy Supply; ADER = Average Dietary Energy Requirement.dAFPS = Average fat and protein supply; RFPI = Recommended fat and protein intake.Variables and goalposts for the Unhealthy Behaviour Index.

This is a metadata only record. The datasets used in this thesis are open and available via https://databank.worldbank.org/source/world-development-indicators We use panel dataset for 115 countries for the time span 1990-2016. The countries are categorized into four groups as per gross national income (GNI) measured using World Bank Atlas (2018) method [the 9 of low ($1005 or less), 32 of lower-middle ($1006-$3955), 35 of upper-middle ($3956-$12,235), and 39 of high ($12,236 or more) income panels]. The data on different variable of interests are collected from World Development Indicators (CD-ROM, 2018). We use real estimation adjusting inflation. The collected datasets of dependent variables are carbon dioxide (CO2) measured in metric tons per capita, methane (CH4) in Kt. of CO2 equivalent, and the particulate matter (PM2.5) in microgram per cubic meter. The independent variables of the collected datasets are gross domestic product (GDP) per capita (constant 2010 US$), energy consumption (EC) in kg of oil equivalent per capita, trade openness (TO) measured as the share of total trade volume in GDP, urbanization (UR) in terms of the share of urban population in total population and TR is the total transport services in percentage of total commercial service of exports and imports, financial development (FD) measured in domestic credit to private sector, foreign direct investment (FDI) is measured by the net inflows of FDI as a percentage of GDP, the human development index (HDI) measured by the UNDP as a proxy for human capital formation. Moreover, we measure the agricultural sector by its output share of GDP (constant 2010 US$) and the manufacturing sector by its output share of GDP (constant 2010 US$).

This paper examines whether green financing creates inclusive growth in Ghana. Quantitative time series data spanning 1990 to 2020 were gathered from secondary sources. Secondary data gathered from World development index, UNDP, UNEP, and IEA were used to establish the link between green financing and inclusive growth in Ghana. CO2 emissions per capita and renewable energy as percentage of total primary energy were used as proxies for green financing whilst human development index, education and life expectancy were used as proxies for inclusive growth. The ARDL techniques were adopted to analyse the data. The study finds that clean energy, CO2 emission reductions and education do not create inclusive growth in Ghana in the short-run. Improvement in the human development index and life expectancy creates inclusive growth both in the short and long run. The study demonstrates that education without appropriate skills and employment avenues would not reduce poverty and spurs on inclusive growth. Purposive sampling approach and desk survey method were adopted to gather the data from the World Bank, United Nations, UNDP, IEA, OECD, IMF, GSS, GLSS, and Ghana Multidimensional Poverty documents for the analysis. Explanatory and descriptive techniques were applied to arrive at the conclusions based on the data collected. To situate this study in context, the human development model was used to link the concepts and variables to arrive at a clear conclusion. This econometric model adopted is convenient for any data size (Odhiambo, 2009). Vector auto regression technique is used and the Granger causality model is applied based on the error-correction mechanisms. The paper used ARDL regression and bound test analysis to assess the interconnection between green financing indicators and inclusive growth. The ARDL regression model works by using one or more independent variables to predict the impacts on dependent variable (Kumari & Yadav, 2018). The connection between dependent variable and one or more independent variables were assessed, and since this paper tested for the impact of green finance indicators on inclusive growth, the use of ARDL regression is fit and proper. The econometric model adopted was: INCGROWTH = β0 +β1CO2EM + β2CLENRG + β3EDU + β4LEXP + β5HDI + εi Methodologically, the estimation focus is on how changes in the green financing might affect inclusive growth in Ghana. It is necessary to expatiate the property of time series variables in the ARDL model to determine how well they work with the preferred estimating method before looking at the results. This is usually done using the Unit Root Test.

Independent variables according to the level of analysis.