Spatial Autoregressive Models

Spatial Autoregressive Models is a class of econometric models that incorporates spatial dependence by specifying a autoregressive process for the dependent variable, where the value of the variable at a given location depends on the values of the variable at neighboring locations through a spatial weights matrix.

700

Publications

58.3K

Citations

1.5K

Authors

756

Institutions

Publications per year

2017–2026

247

Authors

1.5K

  1. DA
    Daniel A. Griffith

    The University of Texas at Dallas, United States

    17 publications · 3.4K citations

    17

    h-index

  2. LL
    Lung‐fei Lee

    The Ohio State University, United States

    15 publications · 1.3K citations

    14

    h-index

  3. IR
    Ingmar R. Prucha

    University of Maryland, College Park, United States

    14 publications · 3.8K citations

    13

    h-index

  4. JP
    James P. LeSage

    Texas State University, United States

    14 publications · 4.8K citations

    13

    h-index

  5. HH
    Harry H. Kelejian

    University of Maryland, College Park, United States

    12 publications · 3.3K citations

    12

    h-index

1–5 of 1.5K

Venues

  1. Journal of Econometrics

    29 publications · 4.8K citations

    25

    h-index

  2. Geographical Analysis

    28 publications · 3.7K citations

    23

    h-index

  3. SSRN Electronic Journal

    Repository · 30 publications · 1.3K citations

    17

    h-index

  4. Regional Science and Urban Economics

    18 publications · 1K citations

    16

    h-index

  5. Papers of the Regional Science Association

    15 publications · 1.8K citations

    15

    h-index

1–5