The United States recorded a Government Debt to GDP of 124.30 percent of the country's Gross Domestic Product in 2024. This dataset provides - United States Government Debt To GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This is the dataset I used to figure out which sociodemographic factor including the current pandemic status of each state has the most significan impace on the result of the US Presidential election last year. I also included sentiment scores of tweets created from 2020-10-15 to 2020-11-02 as well, in order to figure out the effect of positive/negative emotion for each candidate - Donald Trump and Joe Biden - on the result of the election.

Details for each variable are as below: - state: name of each state in the United States, including District of Columbia - elec16, elec20: dummy variable indicating whether Trump gained the electoral votes of each state or not. If the electors casted their votes for Trump, the value is 1; otherwise the value is 0 - elecchange: dummy variable indicating whether each party flipped the result in 2020 compared to that of the 2016 - demvote16: the rate of votes that the Democrats, i.e. Hillary Clinton earned in the 2016 Presidential election - repvote16: the rate of votes that the Republicans , i.e. Donald Trump earned in the 2016 Presidential election - demvote20: the rate of votes that the Democrats, i.e. Joe Biden earned in the 2020 Presidential election - repvote20: the rate of votes that the Republicans , i.e. Donald Trump earned in the 2020 Presidential election - demvotedif: the difference between demvote20 and demvote16 - repvotedif: the difference between repvote20 and repvote16 - pop: the population of each state - cumulcases: the cumulative COVID-19 cases on the Election day - caseMar ~ caseOct: the cumulative COVID-19 cases during each month - Marper10k ~ Octper10k: the cumulative COVID-19 cases during each month per 10 thousands - unemp20: the unemployment rate of each state this year before the election - unempdif: the difference between the unemployment rate of the last year and that of this year - jan20unemp ~ oct20unemp: the unemployment rate of each month - cumulper10k: the cumulative COVID-19 cases on the Election day per 10 thousands - b_str_poscount_total: the total number of positive tweets on Biden measured by the SentiStrength - b_str_negcount_total: the total number of negative tweets on Biden measured by the SentiStrength - t_str_poscount_total: the total number of positive tweets on Trump measured by the SentiStrength - t_str_poscount_total: the total number of negative tweets on Trump measured by the SentiStrength - b_str_posprop_total: the proportion of positive tweets on Biden measured by the SentiStrength - b_str_negprop_total: the proportion of negative tweets on Biden measured by the SentiStrength - t_str_posprop_total: the proportion of positive tweets on Trump measured by the SentiStrength - t_str_negprop_total: the proportion of negative tweets on Trump measured by the SentiStrength - white: the proportion of white people - colored: the proportion of colored people - secondary: the proportion of people who has attained the secondary education - tertiary: the proportion of people who has attained the tertiary education - q3gdp20: GDP of the 3rd quarter 2020 - q3gdprate: the growth rate of the 3rd quarter 2020, compared to that of the same quarter last year - 3qsgdp20: GDP of 3 quarters 2020 - 3qsrate20: the growth rate of GDP compared to that of the 3 quarters last year - q3gdpdif: the difference in the level of GDP of the 3rd quarter compared to the last quarter - q3rate: the growth rate of the 3rd quarter compared to the last quarter - access: the proportion of households having the Internet access

This dataset (dt_elecstds.dta) contains panel data by municipality on infrastructure investment by the Ministry of Public Works, electoral information and socioeconomic variables in Chile for the period 1989-2018. Electoral data includes: three dummies for municipalities' political alignment (a dummy coded one if the mayor belongs to one of the political parties of the central government coalition (m); a dummy coded one if the government coalition parties won presidential elections in the municipality (p); and a dummy coded one if the mayor belongs to one of the coalition parties and the coalition won presidential elections in the municipality (mp)); and two dummies coded one for local ballot years (ym0), and for national ballot years (yp0). The sample comprises seven local (1992, 1996, 2000, 2004, 2008, 2012 and 2016) and seven presidential elections (1989, 1993, 1999, 2005, 2009, 2013 and 2017). Socioeconomic data includes: population (log); regional GDP per capita; regional GDP growth rate in t and t-1; the percentage of new-borns measuring less than 50 cm; the percentage of new-borns weighting less than 3000 gr; and the percentage of mothers with more than three children. In the absence of poverty indicators for the whole sample series, the latter accounted for proxies since they are correlated with municipalities’ socioeconomic conditions (Mardones & Acuña, 2020). Population data is from the National Statistics Institute, GDP data from the Central Bank and poverty proxies from Mardones & Acuña (2020). This dataset has been used to test whether infraestructure investment has been distributed on electoral criteria or not. In particular, it allows to evaluate if the municipalities lined up with the central government coalition parties (m, p and mp dummies) have been systematically benefited, and if allocations increased during local and presidential ballot years (ym0 and yp0 dummies). Since the data goes from the first democratic elections after Pinochet's dictatorship (1989) to 2018, it provides the opportunity to analyse if electoral criteria have changed as democracy entrenched. In particular, it can be tested whether distributions favoured aligned municipalities and whether a political budget cycle persisted during the early years and later. We also include a code file (do_elecstds_050420.do) with several estimations that show how these two electoral distortions evolved during the early years (1989-2005) and once democracy took root (2006-2018). These estimations are part of the paper entitled "Electoral incentives and distributive politics in young democracies: evidence from Chile".

The Gross Domestic Product (GDP) in Philippines expanded 5.40 percent in the first quarter of 2025 over the same quarter of the previous year. This dataset provides - Philippines GDP Annual Growth Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.