kylebutts

## Adapated from bipartitepandas python package
#' Simulate Bipartite Labor Market Network
#'
#' Generates panel data for a bipartite network of workers and firms with
#' assortative matching, mobility, and AKM wage structure.
#'
#' @param n_workers Integer. Number of workers (default: 10000)
#' @param n_time Integer. Panel length in time periods (default: 5)
#' @param firm_size Numeric. Average firm size per period (default: 50)

kylebutts

library(tidyverse)
library(rdrobust)
library(rdlocrand)
hansen <- haven::read_dta(
  "https://github.com/kylebutts/UARK_5783/raw/refs/heads/main/Slides/04_RDD/data/hansen_dwi.dta"
)
est_rdlocrand <- rdlocrand::rdrandinf(
  Y = hansen$recidivism,
  R = hansen$bac1,

kylebutts

Source: https://www.census.gov/geographies/reference-files/time-series/geo/addcountlisting.html

Block-level housing units count for the following dates: June 2022 and biannually for 2023 through 2025

The Address Count Listing Files are available for download from our file transfer protocol (FTP) site. The files include total housing units and total group quarters counts by census tabulation block from the tabs below. They are generated twice a year based on data from July and November and include data for all 50 States, the District of Columbia, Puerto Rico, and the Island Areas.

kylebutts

triangle_info <- function(A, B, C) {
  # Helper function to compute distance between two points
  dist <- function(P, Q) sqrt((P[1] - Q[1])^2 + (P[2] - Q[2])^2)
  
  # Side lengths
  dist_AB <- dist(A, B)
  dist_AC <- dist(A, C)
  dist_BC <- dist(B, C)
  
  # Law of Cosines for each angle

kylebutts

Dev

1. Download the files with gh repo clone posit-dev/positron in some directory
2. npm i from the main directory to install packages
3. npm run watch from the main directory to compile client and extensions (watch-client and watch-extensions). This will run continuously in the background, so you need a second terminal window

Running tests

The npm test-extension takes way too long as it runs all tests. The -g and -l options do not seem to work. Instead, I recommend opening the positron folder with vscode and it will prompt you to install a task running extension.

kylebutts

library(tidyverse)
library(spatstat)
#> Loading required package: spatstat.data
#> Loading required package: spatstat.univar
#> spatstat.univar 3.1-1
#> Loading required package: spatstat.geom
#> spatstat.geom 3.3-5
#> Loading required package: spatstat.random
#> spatstat.random 3.3-2

kylebutts

Law of Rare Events / Poisson Limit Theorem

This famous theorem states that when you have:

• A large number of independent trials ($n \to \infty$)
• Each trial has a small probability of success ($p \to 0$)
• The expected number of successes ($\lambda = np$) remains constant

$\implies$ the number of successes $X$ follows a Poisson distribution with parameter $\lambda$

kylebutts

* https://github.com/py-econometrics/pyfixest/issues/672
. use "~/Downloads/census2000_5pc.dta", clear
(5% Extract from 2000 US Census (from Abadie et al., 2023))

. 
. // set 1
. b1x2 ln_earnings, x1all(educ) x2all(hours)

                                                      Number of obs = 2632838

kylebutts

library(ggplot2)
beta <- seq(-0.2, 0.2, by = 0.001)
exp_minus_1 <- exp(beta) - 1

(plot_pct_change_appxoimation <- ggplot() +
  geom_line(
 aes(x = beta, y = beta, color = "approx"),

kylebutts

# Modified to use `sf` from this article:
# https://rud.is/b/2014/11/16/moving-the-earth-well-alaska-hawaii-with-r/
library(sf)
#> Linking to GEOS 3.11.0, GDAL 3.5.3, PROJ 9.1.0; sf_use_s2() is TRUE
library(tigris)
#> To enable caching of data, set `options(tigris_use_cache = TRUE)`
#> in your R script or .Rprofile.
library(rmapshaper)
library(ggplot2)