cares_allocation_budget_regs_feb2025
Olivia Martin
2025-02-20
Timing: - CARES Act funds should have been received between July - November 2020 [https://dof.ca.gov/budget/covid-19-information/coronavirus-relief-fund-allocations-for-cities-and-counties/]
- 2020 Finance survey was mailed out in November 2020, and was due by
August 2021. [https://www2.census.gov/programs-surveys/gov-finances/tables/2020/2020_methodology.pdf]
- Survey year 2020 covers individual government fiscal years that ended from July 1, 2019, through June 30, 2020.
- So if the CARES act funds were to show up in outlays, it would be in 2021
Distribution of Pct Change in Outlays
Seems like there are some pretty far right outliers
Regressions w/ Outlays % Change 2020-2021 as outcome
X = Log Allocation, < 200% Change
##
## Call:
## lm(formula = outlays_chng_20_21 ~ log_allocation, data = combined %>%
## filter(outlays_chng_20_21 < 2 & outlays_chng_20_21 > -2))
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.84816 -0.07705 -0.01547 0.04885 1.66170
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.016336 0.030186 -0.541 0.588
## log_allocation 0.003566 0.002265 1.574 0.116
##
## Residual standard error: 0.2178 on 1946 degrees of freedom
## Multiple R-squared: 0.001272, Adjusted R-squared: 0.0007587
## F-statistic: 2.478 on 1 and 1946 DF, p-value: 0.1156X = Log Allocation per Pop, < 200% Change
##
## Call:
## lm(formula = outlays_chng_20_21 ~ log_allocation_per_pop, data = combined %>%
## filter(outlays_chng_20_21 < 2 & outlays_chng_20_21 > -2))
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.84928 -0.07719 -0.01993 0.05212 1.66546
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.029923 0.005429 5.512 4.02e-08 ***
## log_allocation_per_pop 0.286543 1.036171 0.277 0.782
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2179 on 1946 degrees of freedom
## Multiple R-squared: 3.93e-05, Adjusted R-squared: -0.0004746
## F-statistic: 0.07647 on 1 and 1946 DF, p-value: 0.7822X = Log Allocation per Pop, < 500% Change
##
## Call:
## lm(formula = outlays_chng_20_21 ~ log_allocation_per_pop, data = combined %>%
## filter(outlays_chng_20_21 < 5 & outlays_chng_20_21 > -2))
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.8538 -0.0807 -0.0235 0.0489 3.6965
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.032682 0.006022 5.427 6.45e-08 ***
## log_allocation_per_pop 0.823921 1.148588 0.717 0.473
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2418 on 1949 degrees of freedom
## Multiple R-squared: 0.0002639, Adjusted R-squared: -0.000249
## F-statistic: 0.5146 on 1 and 1949 DF, p-value: 0.4733Regressions w/ Outlays % Change 2020-2022 as outcome
X = Log Allocation, < 200% Change
##
## Call:
## lm(formula = outlays_chng_20_22 ~ log_allocation, data = combined %>%
## filter(outlays_chng_20_22 < 2 & outlays_chng_20_22 > -2))
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.94134 -0.12439 -0.03571 0.07766 1.84838
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.038844 0.038907 0.998 0.318
## log_allocation 0.003576 0.002918 1.225 0.221
##
## Residual standard error: 0.279 on 1933 degrees of freedom
## Multiple R-squared: 0.000776, Adjusted R-squared: 0.0002591
## F-statistic: 1.501 on 1 and 1933 DF, p-value: 0.2206X = Log Allocation per Pop, < 200% Change
##
## Call:
## lm(formula = outlays_chng_20_22 ~ log_allocation_per_pop, data = combined %>%
## filter(outlays_chng_20_22 < 2 & outlays_chng_20_22 > -2))
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.93959 -0.12755 -0.03604 0.08071 1.85512
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.084334 0.006974 12.093 <2e-16 ***
## log_allocation_per_pop 0.708332 1.330865 0.532 0.595
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2791 on 1933 degrees of freedom
## Multiple R-squared: 0.0001465, Adjusted R-squared: -0.0003707
## F-statistic: 0.2833 on 1 and 1933 DF, p-value: 0.5946X = Log Allocation per Pop, < 500% Change
##
## Call:
## lm(formula = outlays_chng_20_22 ~ log_allocation_per_pop, data = combined %>%
## filter(outlays_chng_20_22 < 5 & outlays_chng_20_22 > -2))
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9620 -0.1458 -0.0564 0.0604 3.6834
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.106715 0.009466 11.274 <2e-16 ***
## log_allocation_per_pop 0.806718 1.810865 0.445 0.656
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.38 on 1948 degrees of freedom
## Multiple R-squared: 0.0001019, Adjusted R-squared: -0.0004114
## F-statistic: 0.1985 on 1 and 1948 DF, p-value: 0.656Regressions w/ Police Exp % Change 2020-2022 as outcome
X = Log Allocation, < 200% Change
##
## Call:
## lm(formula = police_exp_chng_20_22 ~ log_allocation, data = combined %>%
## filter(police_exp_chng_20_22 < 2 & police_exp_chng_20_22 >
## -2))
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.05427 -0.08742 -0.02988 0.03890 1.78111
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.1020319 0.0351781 2.900 0.00377 **
## log_allocation -0.0007556 0.0026409 -0.286 0.77482
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.254 on 1941 degrees of freedom
## Multiple R-squared: 4.217e-05, Adjusted R-squared: -0.000473
## F-statistic: 0.08186 on 1 and 1941 DF, p-value: 0.7748X = Log Allocation per Pop, < 200% Change
##
## Call:
## lm(formula = police_exp_chng_20_22 ~ log_allocation_per_pop,
## data = combined %>% filter(police_exp_chng_20_22 < 2 & police_exp_chng_20_22 >
## -2))
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.05498 -0.08688 -0.03028 0.03956 1.78062
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.09386 0.00634 14.803 <2e-16 ***
## log_allocation_per_pop -0.79784 1.20123 -0.664 0.507
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.254 on 1941 degrees of freedom
## Multiple R-squared: 0.0002272, Adjusted R-squared: -0.0002879
## F-statistic: 0.4411 on 1 and 1941 DF, p-value: 0.5067X = Log Allocation per Pop, < 500% Change
##
## Call:
## lm(formula = police_exp_chng_20_22 ~ log_allocation_per_pop,
## data = combined %>% filter(police_exp_chng_20_22 < 5 & police_exp_chng_20_22 >
## -2))
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.06034 -0.09243 -0.03515 0.03629 2.77249
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.099702 0.006943 14.361 <2e-16 ***
## log_allocation_per_pop -1.099615 1.316623 -0.835 0.404
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2784 on 1945 degrees of freedom
## Multiple R-squared: 0.0003585, Adjusted R-squared: -0.0001555
## F-statistic: 0.6975 on 1 and 1945 DF, p-value: 0.4037