beta_conv | R Documentation |
Given a dataframe of quantitative indicators along time, the unconditional beta convergence is a statistic capturing some important features. A time variable must be present and sorted. Missing values are not allowed. All other columns are indicator values in each considered country.
beta_conv( tavDes, time_0, time_t, all_within = FALSE, timeName = "time", useTau = TRUE )
tavDes |
the sorted dataframe time by countries on the original scale. No other variable besides time and countries' indicator must be present. |
time_0 |
reference time. |
time_t |
target time strictly larger than time_0. |
all_within |
is FALSE if just two different years are considered (default); if more than two years are desired within the specified interval then it must be TRUE ; the reference time remains time_0. |
timeName |
the name of the variable that contains time information. |
useTau |
if TRUE the log ratio of indicator values is divided for the elapsed time (years). |
a list with the value of beta-conv, by OLS (least-squares), the transformed data and standard statistical tests.
# Example 1: # Dataframe in the format years by countries: require(tibble) myTB1 <- tibble::tribble( ~years, ~UK, ~DE, ~IT, 1990, 998, 1250, 332, 1988, 1201, 868, 578, 1989, 1150, 978, 682, 1991, 1600, 1350, 802 ) # Sort the time variable: newdata <- myTB1[order(myTB1$years),] # Beta convergence statistic by considering just two times, e.g. 1989 and 1991: myBC1 <- beta_conv(newdata,1989,1991,timeName="years") # Visualize the summary of the results (estimated coefficients, standard errors, p-values): myBC1$res$summary # Visualize the adjusted R-squared: myBC1$res$adj.r.squared # Beta convergence statistic by considering more than two times: myBC2 <- beta_conv(newdata,1988,1991,all_within=TRUE,timeName="years") # Example 2: # Dataframe in the format years by countries, time variable already sorted: testTB <- tribble( ~time, ~countryA , ~countryB, ~countryC, 2000, 0.8, 2.7, 3.9, 2001, 1.2, 3.2, 4.2, 2002, 0.9, 2.9, 4.1, 2003, 1.3, 2.9, 4.0, 2004, 1.2, 3.1, 4.1, 2005, 1.2, 3.0, 4.0 ) myBC3 <- beta_conv(testTB, time_0 = 2000, time_t = 2005, timeName = "time") myBC4 <- beta_conv(testTB, time_0 = 2000, time_t = 2005, all_within = TRUE, timeName = "time") # Example 3 # Beta convergence for the emp_20_64_MS Eurofound dataset: data(emp_20_64_MS) empBC <- beta_conv(emp_20_64_MS, time_0 = 2002, time_t = 2006, timeName = "time") # Summary of the model results: empBC$res$summary # Adjusted R-squared: empBC$res$adj.r.squared
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