| Smolyak method for solving dynamic economic models: Lagrange interpolation, anisotropic grid and adaptive domain KL Judd, L Maliar, S Maliar, R Valero Journal of Economic Dynamics and Control 44, 92-123, 2014 | 228 | 2014 |
| Numerically stable and accurate stochastic simulation approaches for solving dynamic economic models KL Judd, L Maliar, S Maliar Quantitative Economics 2 (2), 173-210, 2011 | 196* | 2011 |
| Merging simulation and projection approaches to solve high‐dimensional problems with an application to a new Keynesian model L Maliar, S Maliar Quantitative Economics 6 (1), 1-47, 2015 | 114 | 2015 |
| Solving the incomplete markets model with aggregate uncertainty using the Krusell–Smith algorithm L Maliar, S Maliar, F Valli Journal of Economic Dynamics and Control 34 (1), 42-49, 2010 | 104 | 2010 |
| Deep learning for solving dynamic economic models. L Maliar, S Maliar, P Winant Journal of Monetary Economics 122, 76-101, 2021 | 90 | 2021 |
| Numerical methods for large-scale dynamic economic models L Maliar, S Maliar Handbook of computational economics 3, 325-477, 2014 | 88 | 2014 |
| The representative consumer in the neoclassical growth model with idiosyncratic shocks L Maliar, S Maliar Review of Economic Dynamics 6 (2), 362-380, 2003 | 69 | 2003 |
| Parameterized expectations algorithm and the moving bounds L Maliar, S Maliar Journal of Business & Economic Statistics 21 (1), 88-92, 2003 | 68 | 2003 |
| Heterogeneity in capital and skills in a neoclassical stochastic growth model L Maliar, S Maliar Journal of Economic Dynamics and Control 25 (9), 1367-1397, 2001 | 68 | 2001 |
| Merging simulation and projection approaches to solve high-dimensional problems KL Judd, L Maliar, S Maliar National Bureau of Economic Research, 2012 | 58 | 2012 |
| Solving the multi-country real business cycle model using ergodic set methods S Maliar, L Maliar, K Judd Journal of Economic Dynamics and Control 35 (2), 207-228, 2011 | 57 | 2011 |
| Envelope condition method versus endogenous grid method for solving dynamic programming problems L Maliar, S Maliar Economics Letters 120 (2), 262-266, 2013 | 51 | 2013 |
| How to solve dynamic stochastic models computing expectations just once KL Judd, L Maliar, S Maliar, I Tsener Quantitative Economics 8 (3), 851-893, 2017 | 48 | 2017 |
| A cluster-grid projection method: solving problems with high dimensionality KL Judd, L Maliar, S Maliar National Bureau of Economic Research, 2010 | 42 | 2010 |
| Endogenous growth and endogenous business cycles L Maliar, S Maliar Macroeconomic Dynamics 8 (5), 559-581, 2004 | 39 | 2004 |
| Will artificial intelligence replace computational economists any time soon? L Maliar, S Maliar, P Winant CEPR Discussion Paper No. DP14024, 2019 | 37 | 2019 |
| Envelope condition method with an application to default risk models C Arellano, L Maliar, S Maliar, V Tsyrennikov Journal of Economic Dynamics and Control 69, 436-459, 2016 | 36 | 2016 |
| EU eastern enlargement and foreign investment: Implications from a neoclassical growth model K Garmel, L Maliar, S Maliar Journal of Comparative Economics 36 (2), 307-325, 2008 | 35 | 2008 |
| A tractable framework for analyzing a class of nonstationary Markov models L Maliar, S Maliar, J Taylor, I Tsener National Bureau of Economic Research, 2015 | 28 | 2015 |
| Capital-skill complementarity and inequality: Twenty years after L Maliar, S Maliar, I Tsener Economics Letters 220, 110844, 2022 | 23 | 2022 |
