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Table 6 Robustness checks: propensity-score matching method

From: The effect of overseas investors on local market efficiency: evidence from the Shanghai/Shenzhen–Hong Kong Stock Connect

 

(1)

(2)

(3)

(4)

DailySprd1

DailySprd2

HSSC

0.0022***

0.0021***

0.0019***

0.0018***

 

(6.69)

(7.21)

(6.34)

(7.03)

Size

 

0.0028***

 

0.0025***

  

(16.80)

 

(16.44)

Lev

 

 − 0.0077***

 

 − 0.0069***

  

(− 10.44)

 

(− 10.31)

ROA

 

0.0009

 

0.0001

  

(0.35)

 

(0.03)

Cash_vol

 

 − 0.0004***

 

 − 0.0003***

  

(− 3.31)

 

(− 3.07)

Loss

 

0.0005

 

0.0005

  

(1.21)

 

(1.26)

Age

 

0.0006***

 

0.0005***

  

(3.50)

 

(3.18)

Opinion

 

0.0003

 

0.0002

  

(0.46)

 

(0.30)

Analyst

 

 − 0.0010***

 

 − 0.0010***

  

(− 8.64)

 

(− 9.85)

Turnover

 

 − 0.0009***

 

 − 0.0008***

  

(− 31.73)

 

(− 31.52)

_cons

 − 0.0511***

 − 0.0965***

 − 0.0465***

 − 0.0862***

 

(− 45.69)

(− 32.46)

(− 46.66)

(− 32.06)

Industry

Yes

Yes

Yes

Yes

Year

Yes

Yes

Yes

Yes

N

5012

5012

5012

5012

adj. R2

0.682

0.785

0.687

0.787

  1. To mitigate the possible selection bias due to the selection of eligible firms, we adopt the methodology of propensity-score matching (PSM) to match data one to one by eligible firms and non-eligible firms and divide matching data into treatment group and control group. Specifically, we construct a control sample by nearest neighbour propensity score one-to-one matching strategy with a set of firm characteristics, including firm size (Size), book leverage (Lev), profitability (ROA and Loss), cash flows volatility(Cash_vol), listage, audit opinion, analyst following and share turnover. Finally, we obtain the sample comprising 5012 firm-year matching observations. Table 6 reports the results of DID analysis using PSM method
  2. ***, **, and * denote significance at the 1%, 5%, and 10% level, respectively