Machine Learning Methods That Economists Should Know About
Bibliographic Data
| ID | 23347488 |
|---|---|
| Authors | Susan Athey (0000-0001-6934-562X, National Bureau of Economic Research), Guido W Imbens (0000-0002-4846-7326, National Bureau of Economic Research) |
| Year | 2019 |
| Volume | 11 |
| Issue | 1 |
| Pages | 685-725 |
| Publication date | 2019-08-02 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Annual Review of Economics (JOURNAL) |
| Journal identifiers | ISSN: 1941-1383 • E-ISSN: 1941-1391 |
| Publisher | Annual Reviews (PUBLISHER • US) |
| DOI | 10.1146/annurev-economics-080217-053433 |
| OpenAlex | W2922705140 |
| Language | EN |
| Citations received | 127 |
| References cited | 91 |
We discuss the relevance of the recent machine learning (ML) literature for economics and econometrics. First we discuss the differences in goals, methods, and settings between the ML literature and the traditional econometrics and statistics literatures. Then we discuss some specific methods from the ML literature that we view as important for empirical researchers in economics. These include supervised learning methods for regression and classification, unsupervised learning methods, and matrix completion methods. Finally, we highlight newly developed methods at the intersection of ML and econometrics that typically perform better than either off-the-shelf ML or more traditional econometric methods when applied to particular classes of problems, including causal inference for average treatment effects, optimal policy estimation, and estimation of the counterfactual effect of price changes in consumer choice models.
Causal inference · Counterfactual thinking · Econometrics · Economics · Estimation · Inference · Intersection (aeronautics) · Machine learning · Regression · Relevance (law) · Statistics · Advanced Causal Inference Techniques · Artificial Intelligence · Computer Science · Consumer Market Behavior and Pricing · Mathematics · Monetary Policy and Economic Impact · Psychology
How urban amenity factors shape the geography of innovative enterprises
Equitable Evaluation
Disparate Effects of Disruptive Events on Children
Stage Segmentation of Rural Transformation and Comparisons Among Bangladesh, China, Indonesia, and Pakistan
Oksági következtetések
Addressing sample selection bias for machine learning methods
Multiway Cluster Robust Double/Debiased Machine Learning
Estimating heterogeneous treatment effects with item‐level outcome data
Tackling Climate Change with Machine Learning
Decentralising health management
Enhancing Export Competitiveness of SMEs in Sfax
Legitimacy of Algorithmic Decision-Making
A multi-scale story of the diffusion of a new technology
Leveraging the digital layer
Human capital portability and international student migration
Routes to the Top
Predicting the technological complexity of global cities based on unsupervised and supervised machine learning methods
Machine learning in public administration research
When rail matters most
Discrepancies between intention, self-reported behavior, and actual behavior in e-bike helmet wearing
How to promote relative and absolute educational intergenerational mobility? A global study based on interpretable machine learning
Life expectancy and its determinants
Planning for equitable public health
The delayed and combinatorial response of online public opinion to the real world
The effect of sport in online dating
Forecasting food trends using demographic pyramid, generational differentiation and SuperLearner
Environmental-Health Vulnerability and Respiratory Mortality in Europe
The health cost of urbanization
Comparative Evaluation of Estimated Private Rates of Return to General and Vocational Upper Secondary Education in Greece
What Local Environments Drive Opportunities for Social Events? A New Approach Based on Bayesian Modeling in Dallas, Texas, USA
Government Audits and Rural Revitalization
A poisoned gift? The hireability signals of an income-support program for the senior unemployed
How does the entrepreneurship ecosystem foster tourism competitiveness
A Comparison of Different Approaches for Estimating Cross-Lagged Effects from a Causal Inference Perspective
Exploring the Role of Family Environment in Explaining Financial Literacy Levels of Students
How to Use Data Science in Economics – A Classroom Game Based on Cartel Detection
Cultural-tourism integration and ecological product value realization
Living innovation machines
The role of networks and relatedness in the birth of new industries. In search of incomplete innovative arrangements
Machine Labor
Estimating structural spillovers in international trade networks
Predicting household resilience with machine learning
Uncovering heterogeneous regional impacts of Chinese monetary policy
Big data forecasting of South African inflation
The Jedi path to formal economy
Forecasting oil prices with random forests
Business registration from inception and employment indicators using causal machine learning
The use of ICTs and income distribution in Brazil
Using Machine Learning to Create an Early Warning System for Welfare Recipients
Who knows about climate change? Determinants of climate awareness among rural farmers in Zambia using supervised machine learning
What is at stake without high-stakes exams? Students’ evaluation and admission to college at the time of Covid-19
Structural adjustment of industrial land use and economic resilience
Framing of economic news and policy support during a pandemic
Measuring the value of rent stabilization and understanding its implications for racial inequality
City origins
Micro-geographic property price and rent indices
Gotham city. Predicting ‘corrupted’ municipalities with machine learning
Forecasting credit ratings of decarbonized firms
Role of green finance instruments in shaping economic cycles
Effectiveness of tutoring at school
Predicting local taxation decision-making
Machines of justice
Multi‐Criteria Comparability for Ethical and Reliable Measurement of Corporate Environmental Decoupling
Retracted Article
From ashes to opportunity? Reimagining job creation in a smoke-free Africa
How do machines predict energy use? Comparing machine learning approaches for modeling household energy demand in the United States
The Use of Machine Learning Methods in Political Science
The ideal neighbourhoods of successful ageing
Gender Equality, Governance and National Innovation Capability for Sustainable Development
Agricultural Productivity‐Driven Renewable Energy Adoption and Mechanisms in Developing Economies
Impact of Gender Equality and Green Finance on Green Growth
Integrating Street Views, Satellite Imageries and Remote Sensing Data Into Economics and the Social Sciences
Organizing public sector AI adoption
Indigenous and non-Indigenous proficiency gaps for out-of-school and in-school populations
Predicting access to healthful food retailers with machine learning
A review of data linkages for policy-informing research in food and agricultural economics
Good identification, meet good data
Combining survey and census data for improved poverty prediction using semi-supervised deep learning
Poverty mapping in the age of machine learning
Identifying psychological trauma among Syrian refugee children for early intervention
Returns to quality in rural agricultural markets
What do we really know about the drivers of undeclared work? An evaluation of the current state of affairs using machine learning
An s-frame agenda for behavioral public policy research
Identifying and Predicting Nascent High-Growth Firms Using Machine Learning
Transformative policies in Brazilian agri-food systems
How institutional governance shaped the economic recovery after mining disasters in Brazil
Decoding AI innovation
Closing the loop on land
Late With Missing or Mismeasured Treatment
Generalized Autoregressive Score Trees and Forests
Data-driven exploration of heterogeneous gasoline price elasticities using generalized random forests
Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment with High-Dimensional Data
Causal Estimands and Multiply Robust Estimation of Mediated-Moderation
Towards the Ranking of the Importance of Revolutionary Destabilization Factors in Asian and African Countries Using Machine Learning Methods
Digitalisation of International Trade in Intellectual Properties
Narrative forecasts
Loose bricks in the wall
A review and evaluation of internal migration forecasting models
Leveraging machine learning methods to estimate heterogeneous effects
A Pragmatist’s Guide to Using Prediction in the Social Sciences
Causal Inference for Statistics, Social, and Biomedical Sciences
Ensemble Methods in Machine Learning
Econometric Methods for Program Evaluation
Regularization and Variable Selection Via the Elastic Net
Reinforcement Learning
Learning representations by back-propagating errors
Ridge Regression
Least angle regression
Statistical Modeling
Algorithm as 136
Stochastic gradient boosting
Multilayer feedforward networks are universal approximators
Top 10 algorithms in data mining
Recursive partitioning for heterogeneous causal effects
Bart
Support-Vector Networks
Semiparametric Efficiency in Multivariate Regression Models with Missing Data
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
Double/debiased machine learning for treatment and structural parameters
Beyond prediction
Estimating treatment effect heterogeneity in randomized program evaluation
Model-Based Recursive Partitioning
Determining the Number of Factors in Approximate Factor Models
Inferential Theory for Factor Models of Large Dimensions
Bayesian Nonparametric Modeling for Causal Inference
Bagging predictors
Synthetic Control Methods for Comparative Case Studies
The central role of the propensity score in observational studies for causal effects
Random Forests
Deep learning
Regression Shrinkage and Selection Via the Lasso
Regression discontinuity designs
Statistics and Causal Inference
Bias-Corrected Matching Estimators for Average Treatment Effects
Modeling Heterogeneous Treatment Effects in Survey Experiments with Bayesian Additive Regression Trees
Comparative Politics and the Synthetic Control Method
Recent Developments in the Econometrics of Program Evaluation
The State of Applied Econometrics
Big Data
Distributional Structure
Machine Learning
High-Dimensional Methods and Inference on Structural and Treatment Effects
| Unique citing works | 127 |
|---|---|
| Citations per year | 18,14 |
| Citation span | 2019 - 2026 (8) |
| Citation velocity | current |
| Highly cited | Yes |
| Citation types | Neutral: 119 |