Simulation experimental design Firm Choice Dummy Model

The following code shows the selected priors and the corresponding WTP values as well as the deterministic choices

The simulation has 300 respondents and 2000 runs. The simulation itself took 30M 43.8969999999999S .

Statistics and power

Here you see the statistics of the parameters for 2000 runs.

kable(all_designs[["summaryall"]] ,digits = 3) %>% kable_styling()

parname	utilitybayesian.n	utilityfixed.n	truepar	utilitybayesian.mean	utilityfixed.mean	utilitybayesian.sd	utilityfixed.sd	utilitybayesian.min	utilityfixed.min	utilitybayesian.max	utilityfixed.max	utilitybayesian.range	utilityfixed.range	utilitybayesian.se	utilityfixed.se	utilitybayesian.median	utilitybayesian.skew	utilitybayesian.kurtosis	utilityfixed.median	utilityfixed.skew	utilityfixed.kurtosis
bflooddummy1	2000	2000	1.000	1.009	1.005	0.200	0.212	0.228	0.416	1.728	1.775	1.500	1.359	0.004	0.005	1.002	0.121	0.165	0.999	0.113	-0.005
bflooddummy2	2000	2000	1.500	1.505	1.511	0.206	0.236	0.823	0.640	2.175	2.422	1.352	1.782	0.005	0.005	1.502	0.074	-0.173	1.508	0.050	0.116
bheatdummy1	2000	2000	2.700	2.729	2.720	0.220	0.250	1.974	1.855	3.597	3.681	1.624	1.826	0.005	0.006	2.722	0.247	0.292	2.721	0.068	0.091
bheatdummy2	2000	2000	4.650	4.721	4.727	0.425	0.454	3.696	3.784	12.952	13.641	9.256	9.857	0.010	0.010	4.676	4.187	70.190	4.678	7.079	125.809
btax	2000	2000	-0.016	-0.017	-0.016	0.013	0.012	-0.058	-0.053	0.028	0.025	0.086	0.078	0.000	0.000	-0.016	0.046	0.071	-0.017	0.028	0.008
boptout	2000	2000	1.000	1.003	1.001	0.172	0.162	0.487	0.474	1.601	1.587	1.114	1.113	0.004	0.004	1.004	0.081	-0.178	0.997	0.076	0.111
rob_pval0_bflooddummy1	2000	2000	NA	0.000	0.000	0.007	0.002	0.000	0.000	0.260	0.040	0.260	0.040	0.000	0.000	0.000	33.788	1280.189	0.000	10.917	142.353
rob_pval0_bflooddummy2	2000	2000	NA	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.010	0.000	0.010	0.000	0.000	0.000	NaN	NaN	0.000	44.654	1993.003
rob_pval0_bheatdummy1	2000	2000	NA	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	NaN	NaN	0.000	NaN	NaN
rob_pval0_bheatdummy2	2000	2000	NA	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	NaN	NaN	0.000	NaN	NaN
rob_pval0_btax	2000	2000	NA	0.278	0.282	0.281	0.284	0.000	0.000	1.000	1.000	1.000	1.000	0.006	0.006	0.180	0.977	-0.196	0.170	0.930	-0.350
rob_pval0_boptout	2000	2000	NA	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.000	NaN	NaN	0.000	NaN	NaN

all_designs[["powa"]]

$utilitybayesian

FALSE  TRUE 
 73.3  26.7 

$utilityfixed

FALSE  TRUE 
 74.8  25.2 

Illustration of simulated parameter values

To facilitate interpretation and judgement of the different designs, we plot the densities of simulated parameter values from the different experimental designs.

$bflooddummy1

$bflooddummy2

$bheatdummy1

$bheatdummy2

$btax

$boptout