Demonstrate optimal allocation and welfare between two simulated individuals graphically
Test Theorem 1 and Theorem 2 optimal allocation functions when N=2. Use randomly generated A and alpha parameters for two individuals’ discrete and bounded-continuous allocation problems.
Compare welfare between all feasible discrete allocations and possible observed allocations when N=2.
Testing the binary allocation solution line by line and with function. Use standard R testing datasets mtcars and birthwt. Test Welfare (REV) with hand-input example data.
Test binary optimal allocation solution line by line without function. Use the mtcars cars testing dataset. Regress MPG on manual vs auto shift.
Test binary optimal allocation solution function from package. Use the the birthwt testing dataset. Regression birth weight on smoking status.
Line by line, calculate welfare distances, Resource Equivalent Variation (REV), for the Binary Allocation problem based on Theorem 1. Hand-input A and alpha values.
With two individuals of heterogeneous A and alpha, demonstrate the REV comparisons between the actual allocation and optimal allocations by various planners. Work out core concepts.
Demonstrate optimal binary allocation queue. Use empirical A and alpha from the NSW job training RCT from Lalonde (AER, 1986).
Logit employment regression estimation of A and alpha from the Lalonde Training Dataset (722 Observations). Solve for optimal binary allocation queues.
Logit employment regression estimation of A and alpha from the Lalonde Training Dataset (722 Observations). Solve for optimal binary allocation queues by Age only. Using only Age in employment predication and allocation determination.
Linear wage regression estimation of A and alpha from the Lalonde Training Dataset (722 Observations). Solve for optimal binary allocation queues.
Welfare, Resource Equivalent Variation (REV), comparisons between wage and employment allocation results. Wage and Employment allocation space parameters comparison.
Testing the discrete allocation solution line by line and with function. Use the Student Test Score Data from Stock and Watson (2003).
Test discrete optimal allocation solution line by line without function. Use the California student test score dataset. Regress student English and Math test scores on Student-Teacher-Ratio.
Test binary optimal allocation solution function from package. Use the California student test score dataset, same as line by line.
Testing linear-continuous allocation solution line by line and with function. Nutrition and height Data from Puentes et. al. (2016)
Given allocation space parameters (A, alpha), test the lower-bounded continuous optimal allocation line by line without function. This demonstrates relative optimality conditions, inverse optimal allocation, and optimal allocation.
Given allocation space parameters (A, alpha), test the lower-bounded continuous optimal allocation function. Compare inequality measures given optimal allocations across planner preferences.
Test the lower-bounded linear-continuous optimal allocation solution line by line without function. Use the Guatemala-Cebu scrambled nutrition and height early childhood data. Regress the effect of nutritional supplements on height.
Test the lower-bounded linear-continuous optimal allocation solution function from package. Use the Guatemala-Cebu scrambled nutrition and height early childhood data, same as line by line.
Testing log-linear decreasing returns allocation solution line by line and with function. Nutrition and height Data from Puentes et. al. (2016). Results not included in the paper. Results not closed-form, requires root search.
Given allocation space parameters (A, alpha) for log linear regression, test log-linear optima allocation line by line. The result is not included in the final version of the paper, because the results are not closed-form, but are based on a root search. The root search is very fast when initial condition is zero.
Vignette that only conducts estimations and generate A and alpha for estimation space. Most A and alpha generated in various other files as well that also solve for optimal allocation.
Generate A and alpha based on a linear regression. Four categories based on initial height and mother education levels (Guatemala and Cebu dataset). Regress height on protein inputs allowing for heterogeneous effects for each of the four categories.
Vignette that test functions related to the Economic Stimulus Act off 2008 for Nygård, Sørensen and Wang (2021)
In 2008, the Bush administration sent out stimulus checks as tax rebates. The checks are a function of income, marital status, and the number of children. We have functions that computable taxable income given income, tax liability given income, and also stimulus amount given income.