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Table 3 Descriptive statistics of control variables and corresponding t-test results

From: COVID-19 shock, fiscal subsidies, and consumption resilience of new energy vehicles: evidence from Shanghai, China

Variables

(1)

(2)

(3)

(4)

(5)

(6)

(7)

Full sample

-Before COVID-19

Full

sample

-After

COVID-19

Subsided NEVs

-Before

COVID-19

Subsided NEVs

-After

COVID-19

Non-subsided NEVs

-Before COVID-19

Non-subsided NEVs

-After COVID-19

Local smoothness test

Price

36.202

30.213

20.296

20.424

78.871

61.309

0.297

(0.937)

(0.691)

(0.277)

(0.225)

(2.315)

(2.215)

(3.667)

Range

227.162

283.740

237.047

292.319

200.644

256.489

6.728

(4.077)

(4.071)

(4.147)

(4.499)

(9.979)

(9.095)

(21.215)

Engine

0.617

0.673

0.699

0.700

0.399

0.587

0.002

(0.012)

(0.011)

(0.014)

(0.012)

(0.024)

(0.024)

(0.068)

Brand

0.231

0.181

0.017

0.010

0.805

0.725

0.025

(0.011)

(0.009)

(0.004)

(0.003)

(0.019)

(0.021)

(0.050)

Firm

2.978

2.862

3.441

3.186

1.738

1.835

− 0.024

(0.033)

(0.032)

(0.035)

(0.036)

(0.030)

(0.043)

(0.214)

Typecar

2.461

2.381

2.483

2.372

2.401

2.411

0.018

(0.015)

(0.014)

(0.017)

(0.016)

(0.032)

(0.029)

(0.085)

Fuel

1.957

1.760

1.826

1.735

2.308

1.839

− 0.019

(0.025)

(0.023)

(0.029)

(0.026)

(0.046)

(0.046)

(0.130)

Drive

1.646

1.610

1.302

1.369

2.567

2.376

− 0.023

(0.024)

(0.022)

(0.022)

(0.022)

(0.038)

(0.043)

(0.116)

  1. Values without parentheses represent the mean of the variable, while values in parentheses represent standard errors
  2. Source: Authors’ computation using STATA 17