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Data and code for SOC504 replication project
includes the less than 2500 localidad variable.
Data cleaning to find sample of municipalities. Ended with a different number of municipalities than Villarreal found, so not sure what I’m doing wrong.
Sampling Municipalities
…in towns of less than 2500 inhabitants, table with muncodes to match distritos en Oaxaca.
…ities(distritos) with rural table. total 697 municipalities that meet the criterion.
Added some more notes and ideas
Doctors, Female-headed households, indigenous language speakers, homicides. Homicides code doesn’t work yet, need to do a dataset join first and I didn’t have time tonight to learn that!
Added variables from censo
Added dummy variable for DF, don’t think we have the right data for illiteracy or % young males…some comments to that effect at the end.
DF -> State of Mexico
added dummy variable for df
… variables and dependent variable.
Added some notes at the bottom about where in the censor agricola I THINK we can find variables we need, and what data i think we do not currently have…would you be willing to take a look and check my thinking? Or have you already done this?
and then created composite sample data frame with everything
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| ```{r, results='asis'} | ||
| gsub("\n[[:space:]]","", htmlreg(list(extract.negbin(One.a), extract.negbin(One.b), extract.negbin(One.c)), caption = "Table 1: Coefficients from the Negative Binomial Regression Models of Homicide on Land Scarcity and Inequality (Hypotheses 1 and 2)", caption.above = TRUE, stars = c(.05, .01), custom.coef.names = c("Constant", "% units less than or equal to 5 hectares", "Thiel's land inequality", "Log maize yields", "Log population density", "% young males", "% indigenous", "Illiteracy rate", "% female-headed households", "Medical doctors per 10,000", "Valley of Mexico", "Log average plot size", "Log persons per hectare"), custom.note = "SEs in parentheses, * P < .05, ** P < .01, two-tailed tests", include.intercept = TRUE, reorder.coef = c(2, 12, 13, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1), groups = list("Plot size and crop yields" = 1:5, "Demographic variables" = 6:8, "Resource deprivation" = 9, "Family structure" = 10, "Access to medical attention" = 11, "Geographical region" = 12), inline.css = TRUE, doctype = FALSE, html.tag = FALSE, head.tag = FALSE, body.tag = FALSE, center = FALSE, digits = 4, star.symbol = "\\*")) |
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you you break this up so that each option is a new line so it is easier to read?
… turned logs into natural logs.
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