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Table 1 Total effects of SARS input-output flows estimated using an adjusted spatial econometric interaction model

From: Modelling input-output flows of severe acute respiratory syndrome in mainland China

 

SARS input-output flow

Hospitalized flow

Migrant flow

Coefficient

p-value

Coefficient

p-value

Coefficient

p-value

Spatial dependence

ρo

0.201

0.000

0.054

0.218

0.181

0.000

ρd

0.034

0.461

0.171

0.000

0.134

0.002

ρw

0.005

0.947

−0.149

0.032

0.092

0.188

Total effects

const

−9.176

0.000

−3.984

0.033

−6.844

0.002

ai

−27.053

0.001

−20.852

0.001

−23.875

0.002

o_ Urban rate

−0.172

0.703

0.492

0.134

0.116

0.775

o_PGDP

1.121

0.005

0.364

0.201

0.526

0.125

o_Density

−0.108

0.169

−0.091

0.118

−0.006

0.935

o_Road cap

0.079

0.336

0.074

0.232

0.022

0.760

o_Railway cap

0.235

0.034

0.030

0.702

0.084

0.385

o_Flight cap

−0.104

0.176

0.030

0.594

−0.078

0.258

o_Urban income

2.343

0.002

1.114

0.049

0.740

0.262

o_Rural income

−2.474

0.001

−1.162

0.039

−1.204

0.074

d_ Urban rate

0.816

0.047

0.215

0.471

0.988

0.009

d_PGDP

0.238

0.321

0.176

0.315

0.083

0.696

d_Density

0.003

0.959

−0.010

0.825

−0.067

0.230

d_Road cap

0.168

0.054

0.066

0.299

0.131

0.086

d_Railway cap

−0.093

0.347

0.035

0.628

0.014

0.874

d_Flight cap

−0.060

0.441

−0.117

0.055

−0.112

0.112

d_Urban income

1.197

0.105

0.681

0.221

2.318

0.001

d_Rural income

−0.908

0.141

−0.649

0.159

−1.516

0.007

distance

−0.157

0.116

−0.176

0.015

−0.129

0.165

i_ Urban rate

3.041

0.210

2.372

0.186

3.804

0.087

i_PGDP

−1.181

0.540

−3.206

0.035

1.167

0.495

i_Density

−0.100

0.800

−0.268

0.358

−0.349

0.326

i_Road cap

0.230

0.578

−0.205

0.497

0.533

0.154

i_Railway cap

1.402

0.003

0.787

0.025

1.612

0.000

i_Flight cap

−0.642

0.108

−0.813

0.009

−0.779

0.034

i_Urban income

8.357

0.023

7.424

0.010

7.521

0.023

i_Rural income

−2.290

0.530

1.136

0.675

−5.687

0.085

R 2

0.393

 

0.523

 

0.479

 

\( {\overline{R}}^2 \)

0.371

 

0.506

 

0.460

 

log-likelihood

−160.094

 

−24.251

 

−50.304

 

Nobs, Nvars

729,

27