Table 5.

Possible Mechanisms: 2008–2009.

	(1) State-level Expenditures	(2) Federal Expenditures	(3) Oral Rehydration Salts	(4) Vaccines	(5) Hospital Beds	(6) Google Searchesc	(7) Google Searchesc
H1N1/1000a	0.027	0.006	−0.086	−0.025	−0.006	3.156	3.111
	(0.013)	(0.005)	(0.062)	(0.037)	(0.023)	(1.134)	(1.057)
p-valueb	0.724	0.889	0.152	0.502	0.812	0.106	0.085
R2	0.285	0.137	0.627	0.682	0.073	0.458	0.451
Mean$\left({\displaystyle \overline{Y}}\right)$	8.194	5.998	14.518	14.518	6.693	7.63	5.72
Obs.	64	64	64	64	64	48	64

Notes: Each column represents a separate regression. All regressions include time and state fixed effects. Mean $\left({\displaystyle \overline{Y}}\right)$ denotes the mean of the dependent variable for each specification and for the period 2008–2009.

^aParameters for columns (1)–(5) capture the association per 1000 cases of H1N1. The dependent variable in columns (6) and (7) captures the intensity of search volume per state and year, which ranges from 0 to 100. The dependent variable in columns (1)–(5) is the log of the outcome of interest. Columns (1) and (2) denote the log of millions of expenditures in Mexican pesos.

^bp-value denotes the p-value of wild bootstrapped standard errors for each specification to correct for small number (32) of clusters.

^cIn columns (6) the specifications exclude the states of Baja California Sur, Campeche, Colima, Chihuahua, Durango, Nayarit, Tlaxcala, and Zacatecas for which Google data were missing. In column (7) we assigned a value of zero to states with missing Google searches.