Results from estimates using Equation (1)
| Categories | |||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| All | 1101 | 1102 | 1103 | 1104 | 1105 | 1106 | 1107 | 1108 | 1109 | 1110 | 1111 | 1112 | 1113 | 1114 | 1115 | 1116 | |
| 0.001 | −0.104 | −0.088 | −0.907 | 0.315*** | 0.129 | −0.083 | 0.046 | 0.152 | −0.064 | 0.012 | 0.200 | −0.039 | 0.183 | 0.497** | 0.048 | ||
| (0.053) | (0.206) | (0.087) | (0.709) | (0.042) | (0.144) | (0.066) | (0.146) | (0.113) | (0.069) | (0.028) | (0.155) | (0.058) | (0.158) | (0.196) | (0.137) | ||
| 0.011 | −0.079 | 0.665*** | 0.395*** | 0.111 | 0.011 | −0.131 | 0.042 | 0.043 | −0.112 | 0.115 | 0.103 | 0.002 | |||||
| (0.024) | (0.071) | (0.172) | (0.043) | (0.106) | (0.012) | (0.095) | (0.053) | (0.042) | (0.071) | (0.210) | (0.079) | (0.116) | |||||
| 0.026 | −0.076* | 0.131 | 0.311*** | 0.139** | −0.002 | 0.160 | 0.055* | −0.029 | 0.101** | 0.289 | −0.163*** | −0.078 | |||||
| (0.019) | (0.046) | (0.202) | (0.047) | (0.063) | (0.059) | (0.107) | (0.030) | (0.042) | (0.043) | (0.330) | (0.048) | (0.052) | |||||
| 0.030* | 0.341*** | 0.230*** | 0.026 | 0.179** | 0.056 | 0.026 | −0.039 | −0.153 | −0.012 | 0.163*** | |||||||
| (0.018) | (0.077) | (0.037) | (0.029) | (0.069) | (0.072) | (0.040) | (0.069) | (0.098) | (0.099) | (0.042) | |||||||
| 0.062** | 0.125 | 0.323*** | 0.015 | 0.059 | −0.008 | −0.073 | −0.083 | 0.347** | 0.338* | ||||||||
| (0.027) | (0.148) | (0.039) | (0.019) | (0.069) | (0.031) | (0.140) | (0.093) | (0.145) | (0.200) | ||||||||
| 0.267** | 0.245*** | 0.040* | 0.042 | 0.052** | 0.042 | 0.092*** | 0.032 | ||||||||||
| (0.133) | (0.040) | (0.023) | (0.042) | (0.022) | (0.058) | (0.024) | (0.053) | ||||||||||
| 0.266*** | 0.062** | −0.047* | 0.234** | 0.304*** | |||||||||||||
| (0.058) | (0.028) | (0.026) | (0.110) | (0.107) | |||||||||||||
| Accumulated effect | 0.130* | −0.104 | −0.243** | 0.889 | 1.819*** | 0.379*** | 0.007 | 0.254 | 0.152 | 0.251* | 0.096 | 0.072 | −0.039 | 0.677 | 1.109*** | 0.473 | |
| (0.078) | (0.206) | (0.116) | (0.623) | (0.109) | (0.106) | (0.121) | (0.310) | (0.113) | (0.130) | (0.105) | (0.176) | (0.058) | (0.451) | (0.292) | (0.301) | ||
| Number of observations | 70,909 | 2,563 | 4,379 | 9,303 | 949 | 4,890 | 12,504 | 12,429 | 2,802 | 4,935 | 2,457 | 5,159 | 2,020 | 2,471 | 1,216 | 1,228 | 1,879 |
| Number of products | 79 | 3 | 4 | 11 | 1 | 6 | 14 | 14 | 4 | 6 | 2 | 6 | 2 | 2 | 1 | 1 | 2 |
| Categories | |||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| All | 1101 | 1102 | 1103 | 1104 | 1105 | 1106 | 1107 | 1108 | 1109 | 1110 | 1111 | 1112 | 1113 | 1114 | 1115 | 1116 | |
| 0.001 | −0.104 | −0.088 | −0.907 | 0.315*** | 0.129 | −0.083 | 0.046 | 0.152 | −0.064 | 0.012 | 0.200 | −0.039 | 0.183 | 0.497** | 0.048 | ||
| (0.053) | (0.206) | (0.087) | (0.709) | (0.042) | (0.144) | (0.066) | (0.146) | (0.113) | (0.069) | (0.028) | (0.155) | (0.058) | (0.158) | (0.196) | (0.137) | ||
| 0.011 | −0.079 | 0.665*** | 0.395*** | 0.111 | 0.011 | −0.131 | 0.042 | 0.043 | −0.112 | 0.115 | 0.103 | 0.002 | |||||
| (0.024) | (0.071) | (0.172) | (0.043) | (0.106) | (0.012) | (0.095) | (0.053) | (0.042) | (0.071) | (0.210) | (0.079) | (0.116) | |||||
| 0.026 | −0.076* | 0.131 | 0.311*** | 0.139** | −0.002 | 0.160 | 0.055* | −0.029 | 0.101** | 0.289 | −0.163*** | −0.078 | |||||
| (0.019) | (0.046) | (0.202) | (0.047) | (0.063) | (0.059) | (0.107) | (0.030) | (0.042) | (0.043) | (0.330) | (0.048) | (0.052) | |||||
| 0.030* | 0.341*** | 0.230*** | 0.026 | 0.179** | 0.056 | 0.026 | −0.039 | −0.153 | −0.012 | 0.163*** | |||||||
| (0.018) | (0.077) | (0.037) | (0.029) | (0.069) | (0.072) | (0.040) | (0.069) | (0.098) | (0.099) | (0.042) | |||||||
| 0.062** | 0.125 | 0.323*** | 0.015 | 0.059 | −0.008 | −0.073 | −0.083 | 0.347** | 0.338* | ||||||||
| (0.027) | (0.148) | (0.039) | (0.019) | (0.069) | (0.031) | (0.140) | (0.093) | (0.145) | (0.200) | ||||||||
| 0.267** | 0.245*** | 0.040* | 0.042 | 0.052** | 0.042 | 0.092*** | 0.032 | ||||||||||
| (0.133) | (0.040) | (0.023) | (0.042) | (0.022) | (0.058) | (0.024) | (0.053) | ||||||||||
| 0.266*** | 0.062** | −0.047* | 0.234** | 0.304*** | |||||||||||||
| (0.058) | (0.028) | (0.026) | (0.110) | (0.107) | |||||||||||||
| Accumulated effect | 0.130* | −0.104 | −0.243** | 0.889 | 1.819*** | 0.379*** | 0.007 | 0.254 | 0.152 | 0.251* | 0.096 | 0.072 | −0.039 | 0.677 | 1.109*** | 0.473 | |
| (0.078) | (0.206) | (0.116) | (0.623) | (0.109) | (0.106) | (0.121) | (0.310) | (0.113) | (0.130) | (0.105) | (0.176) | (0.058) | (0.451) | (0.292) | (0.301) | ||
| Number of observations | 70,909 | 2,563 | 4,379 | 9,303 | 949 | 4,890 | 12,504 | 12,429 | 2,802 | 4,935 | 2,457 | 5,159 | 2,020 | 2,471 | 1,216 | 1,228 | 1,879 |
| Number of products | 79 | 3 | 4 | 11 | 1 | 6 | 14 | 14 | 4 | 6 | 2 | 6 | 2 | 2 | 1 | 1 | 2 |
Note(s): This table presents the results from the estimation of the model described in Equation (1) for products whose prices were collected in at least two metropolitan regions during the period. The values for the constants, the fixed effects (for product-month-year, month, metropolitan region and month-region), and the parameters associated with the cost variables were omitted for convenience. refers to the parameters associated with the k-th lag of the variation of the ICMS nominal rate. The cumulative effect is the sum of the parameters related to all lags included in the models. The maximum number for lags () chosen using the sequential procedure described in Han et al. (2017), with . No product in category 1103 experienced alterations in tax rate, preventing the estimation of a pass-through rate of ICMS to prices. The standard deviations, robust for heteroscedasticity, serial autocorrelation and spatial dependence (Driscoll and Kraay, 1998), are in parentheses. The symbols *, ** and *** indicate parameters statistically different from zero at 10, 5 and 1% significance level, respectively
Source(s): Authors’ elaboration
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