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. Author manuscript; available in PMC: 2019 Mar 1.
Published in final edited form as: Res Econ. 2017 May 31;72(1):1–32. doi: 10.1016/j.rie.2017.05.006

Table 13.

Estimation Results for Main Outcomes, Comparison to No Infant-Toddler Care, Child Cohort

Within Reggio
With Parma
With Padova
None BIC Full PSMR. KMR DidPm KMDidPm KMPm DidPv KMDidPv KMPv
IQ Factor 0.55 0.47 0.35 0.25 0.31 0.34 0.34 −0.21 −0.57 −1.28 0.84
Unadjusted P-Value (0.00)*** (0.01)** (0.06)** (0.12)* (0.18) (0.20) (0.18) (0.36) (0.10)** (0.02)*** (0.01)***
Stepdown P-Value (0.01)*** (0.05)*** (0.29) (0.56) (0.76) (0.79) (0.86) (0.92) (0.50) (0.12) (0.10)
SDQ Composite – Child 0.55 1.04 0.95 1.02 1.24 1.19 1.20 −0.74 0.26 0.92 1.73
Unadjusted P-Value (0.50) (0.20) (0.28) (0.23) (0.17) (0.35) (0.42) (0.52) (0.86) (0.66) (0.08)**
Stepdown P-Value (0.84) (0.82) (0.72) (0.76) (0.76) (0.89) (0.91) (0.92) (0.98) (0.96) (0.31)
Not Obese 0.29 0.22 0.10 0.14 0.17 0.15 0.10 −0.10 −0.13 −0.42 0.38
Unadjusted P-Value (0.00)*** (0.02)*** (0.33) (0.08)** (0.12)* (0.27) (0.44) (0.39) (0.44) (0.10)* (0.00)***
Stepdown P-Value (0.00)*** (0.11) (0.72) (0.47) (0.64) (0.82) (0.92) (0.92) (0.91) (0.31) (0.06)**
Not Overweight −0.06 −0.02 0.02 −0.02 −0.05 0.10 0.09 −0.05 −0.13 −0.15 −0.03
Unadjusted P-Value (0.30) (0.69) (0.80) (0.73) (0.38) (0.29) (0.44) (0.54) (0.09)** (0.23) (0.64)
Stepdown P-Value (0.78) (0.92) (0.93) (0.87) (0.83) (0.89) (0.92) (0.92) (0.71) (0.87) (0.91)
Health is Good −0.11 −0.06 −0.08 −0.08 −0.13 −0.01 −0.05 0.15 −0.02 0.02 −0.14
Unadjusted P-Value (0.20) (0.45) (0.48) (0.40) (0.18) (0.96) (0.75) (0.26) (0.92) (0.94) (0.21)
Stepdown P-Value (0.71) (0.88) (0.72) (0.83) (0.76) (0.94) (0.92) (0.90) (0.98) (0.96) (0.63)
Not Excited to Learn 0.00 −0.01 0.01 −0.02 0.01 −0.07 −0.05 0.03 0.11 0.42 −0.14
Unadjusted P-Value (0.95) (0.71) (0.73) (0.65) (0.79) (0.11)* (0.30) (0.16) (0.09)** (0.05)** (0.07)**
Stepdown P-Value (0.96) (0.92) (0.93) (0.87) (0.93) (0.79) (0.86) (0.77) (0.50) (0.12) (0.30)
Problems Sitting Still −0.10 −0.07 −0.12 −0.04 −0.04 −0.19 −0.18 −0.03 −0.27 −0.20 −0.04
Unadjusted P-Value (0.15) (0.30) (0.12)* (0.48) (0.61) (0.08)** (0.10)* (0.78) (0.05)*** (0.21) (0.59)
Stepdown P-Value (0.54) (0.84) (0.33) (0.86) (0.92) (0.56) (0.57) (0.92) (0.18) (0.87) (0.91)
How Much Child Likes School 0.11 0.08 0.01 0.09 −0.02 0.15 −0.08 −0.11 0.20 −0.37 0.44
Unadjusted P-Value (0.25) (0.38) (0.95) (0.35) (0.86) (0.31) (0.69) (0.37) (0.38) (0.38) (0.00)***
Stepdown P-Value (0.73) (0.88) (0.96) (0.83) (0.93) (0.89) (0.92) (0.92) (0.85) (0.88) (0.06)**
Num. of Friends 0.86 0.79 0.70 0.88 0.87 1.40 1.36 −0.76 0.38 1.31 −0.92
Unadjusted P-Value (0.01)*** (0.02)*** (0.12)* (0.02)*** (0.01)*** (0.04)*** (0.09)** (0.30) (0.78) (0.44) (0.21)
Stepdown P-Value (0.12) (0.23) (0.43) (0.16) (0.07)** (0.35) (0.63) (0.91) (0.97) (0.91) (0.63)
Candy Game: Willing to Share Candies 0.01 0.06 0.00 0.09 0.08 0.09 0.15 −0.09 −0.05 0.05 0.01
Unadjusted P-Value (0.84) (0.31) (0.96) (0.29) (0.30) (0.27) (0.19) (0.15) (0.62) (0.78) (0.91)
Stepdown P-Value (0.96) (0.88) (0.98) (0.78) (0.79) (0.89) (0.84) (0.77) (0.97) (0.96) (0.93)

Note 1: This table shows the estimates of the coefficient for attending Reggio Approach infant-toddler centers from multiple methods. We compare individuals who attended both municipal infant-toddler centers and preschools (1,1) with individuals who only attended municipal preschools and no infant-toddler center (0,1). The Column titles indicate the corresponding control set and and model. None = within-Reggio Emilia OLS estimate with no control variables. BIC = within-Reggio Emilia OLS estimate with controls selected by Bayesian Information Criterion (BIC) and additional controls for male indicator and ITC attendance indicator. Full = within-Reggio Emilia OLS estimate with the full set of controls. PSM = within-Reggio Emilia propensity score matching estimation. KM = within-Reggio Emilia Epanechnikov kernel matching estimation. DidPm = difference-in-differences estimates of (Reggio (1,1) – Reggio (0,1)) – (Parma (1,1) – Parma (0,1)). KMDidPm = difference-in-differences kernel matching estimates of (Reggio (1,1) – Reggio (0,1)) – (Parma (1,1) – Parma (0,1)). KMPm = Epanechnikov kernel matching estimation between Reggio (1,1) and Parma (0,1). DidPv = difference-in-differences estimates of (Reggio (1,1) – Reggio (0,1)) – (Padova (1,1) – Padova (0,1)). KMDidPv = difference-in-differences kernel matching estimates of (Reggio (1,1) – Reggio (0,1)) – (Padova (1,1) – Padova (0,1)).

Note 2: Both unadjusted p-value and stepdown p-value are reported. ***, **, and * indicate significance of the coefficients at the 15%, 10%, and 5% levels respectively. Empty cells show that the estimation cannot be carried out for that outcome.