Applied Econometrics Training Course

Did you know that applied econometrics underpins real-world tools like the Sheffield Alcohol Policy Model that linked a 50 pence minimum unit price to a 5.7% drop in alcohol consumption and thousands fewer hospital admissions, bank stress-testing models that forecast multi‑quarter portfolio losses for regulatory reviews, and labor and education studies that quantify how minimum wage laws affect employment and how schooling raises earnings giving policymakers hard numbers rather than guesswork?

Course Overview

The Applied Econometrics Training Course by Rcademy is designed to equip policy experts, policy professionals, economists, financial professionals, managers, economic trainers, economic undergraduates, and any interested professionals with comprehensive understanding of econometric theory through real-world problem-solving and applications, statistical parameters used in regression evaluation, regulatory tools and macroprudential instruments in mitigating systemic risk, and major theoretical explanations and empirical evidence for causes and consequences of financial problems. Participants gain expert knowledge of translating economic relationships into quantitative statements using regression models, designing econometric models that combine economic intuition with robust statistics, implementing stress-testing frameworks for forward-looking capital planning, and communicating modeling results to ministers, executives, and regulators with appropriate uncertainty representation.​

Without specialized applied econometrics training, professionals may struggle to estimate how much employment changes when minimum wage is raised, quantify how strongly years of schooling affect earnings, design econometric models that capture complex system dynamics like alcohol market responses to pricing policies, forecast balance sheet variables under severe macroeconomic scenarios, or distinguish between correlation and causation in policy evaluation, limiting their ability to provide evidence-based recommendations and satisfy regulatory requirements. This comprehensive course provides a structured path to mastery across mathematics of econometrics with differential calculus and matrix algebra, macroeconomics including fiscal policies and business cycles, labour economics including wage theories and collective bargaining, microeconomics including individual behaviour and marketplace interactions, hypothesis testing with empirical formulas and statistical software, econometrics including limited dependent variables and time-series techniques, economic development surveying, econometrics for the public including political economy and deficit financing, and gaining economic stability through understanding financial system contributions and macroprudential policy, preparing attendees to lead policy evaluation, risk management, and quantitative analysis initiatives.​

Real-world cases show how the University of Sheffield’s Sheffield team developed the Sheffield Alcohol Policy Model for the UK Department of Health, combining an econometric price-to-consumption module with an epidemiological consumption-to-harm module to project the effects of policies like minimum unit pricing on hospital admissions, crime, and mortality, with the model estimating that setting MUP at 50 pence per unit would reduce alcohol consumption and prevent thousands of hospital admissions annually, and these figures became central to public and parliamentary debates.

Studies also show that applied econometrics case studies describe how economists use large datasets and regression models to estimate the effect of minimum wage laws on employment and the impact of education on earnings, with researchers studying changes in minimum wages across regions and over time to see how low-wage job numbers respond, using micro data on individuals’ schooling, experience, and wages to separate the “return to education” from other factors.

Take charge of your econometric expertise. Enroll now in the Rcademy Applied Econometrics Training Course to master the quantitative skills that drive evidence-based policy and strategy.

Who Should Attend?

The Applied Econometrics Training Course by Rcademy is ideal for:

• Policy experts and policy professionals
• Economists and economic analysts
• Financial professionals and financial analysts
• Managers in government and private sector
• Economic trainers and educators
• Economic undergraduates and postgraduates
• Data scientists and statisticians
• Risk managers and quants
• Regulatory policy specialists
• Management consultants
• Central bank professionals
• Research analysts
• Anyone seeking comprehensive econometrics certification

What are the Training Goals?

The main objectives of the Applied Econometrics Training Course are to enable professionals to:

• To estimate statistical parameters used in regression evaluation using the necessary software.
• Correctly interpret empirical papers from leading economists written under a single equation regression model.
• Gain active knowledge of the implications of regulatory tools and macroprudential in mitigating systemic risk from indirect and direct effects.
• Derive statistical parameters that can be used in estimating causal relationships.
• Conduct hypothesis testing at confidence intervals and correctly interpret the results of the findings.
• Gain a deep understanding of the major theoretical explanations and the empirical evidence that exists for the cause and consequences of financial problems.
• Understand the econometrics theory through real-world problem-solving and applications rather than complex proofs and mathematical theorems.
• Grasp the ideas of microeconomics and macroeconomics and how they contribute to the stability and instability of an economy.
• Learn how to interact with data and data sets from banks and the world governments.
• Understand issues of moral hazard, implicit subsidies, and incentives as they are used in the regulation of the financial system and analysis of its empirical literature.
• Manipulate and plot different types of data.
• Use cross-country data sets together with bank data panels to solve real-world problems.
• Understand the interrelationship between the market, banking, and the financial system.
• Learn how to solve simultaneous equation problems and various models that are utilised in econometrics.
• Select the appropriate model according to the data type present.
• Learn to make ethical, impactful, and profitable decisions in the global and local economy.

How Will This Training Course Be Presented?

At Rcademy, the extensive focus is laid on the relevance of the training content to the audience. Thus, content is reviewed and customised as per the professional backgrounds of the audience.

The training framework includes:

• Expert-led lectures by econometrics and quantitative analysis professionals using audio-visual sessions
• Hands-on exercises with statistical software including Stata for regression analysis and hypothesis testing
• Interactive workshops for model calibration, variable selection, and causal inference design
• Case studies covering Sheffield Alcohol Policy Model for minimum unit pricing, U.S. bank CCAR stress-testing with econometric loss models, and minimum wage and education policy evaluation
• Practical simulations for time-series forecasting, panel data analysis, and limited dependent variable modeling

The theoretical part of training is delivered by an experienced professional from the relevant domain, using audio-visual presentations including video presentations, assignments, exercises, group discussions, and case studies. This econometrics-focused approach ensures professionals translate theory into practical workflows through regression evaluation, policy impact estimation, and quantitative model development.​

This comprehensive certification model ensures participants gain both econometrics fundamentals and hands-on proficiency to immediately apply quantitative expertise in policy evaluation, financial risk management, economic research, and regulatory compliance roles.​

Register now to experience a rigorous, hands-on learning journey designed to equip you for leading econometric analysis, policy evaluation, and quantitative decision-making initiatives.

Course Syllabus

Module 1: Introduction to Mathematics of Econometrics

• Differential calculus
• Matrix algebra
• Logarithm in economics
• Linear models
• Comparative static analysis of nonlinear models
• Multivariate differential calculus
• Applications of economics
• Introduction to probability and random variables for econometrics​
• Law of large numbers and central limit theorem for inference​
• Matrix formulation of the regression model​

Module 2: Theory of Macroeconomics

• Fiscal policies
• Financial crisis
• Unemployment
• Income determination
• Debt dynamics
• Long-run growth
• Monetary policies
• Business cycles
• Interaction between monetary and fiscal policy in stabilisation​
• Empirical indicators for tracking macroeconomic performance​
• Using time-series data to study growth and cycles​

Module 3: Labour Economics

• Collective bargaining
• Labour courts
• Wages
• Empirical Studies of wage differentials
• Contemporary theories of wages
• The effect of collective bargaining
• Theories of employment
• Contemporary theories of prices
• Econometric analysis of the gender pay gap and discrimination​
• Estimating labour supply and labour demand elasticities​
• Panel data methods for analysing wage dynamics over time​

Module 4: The Theory of Microeconomics

• The government, through the economy’s eyes
• Individual behaviour
• Foundations of Microeconomic theories
• Economic efficiency of an assortment of public policies
• The Role of Government in the Economy
• The behaviour of firms
• Marketplace interactions
• Forms of market structures
• Public Policies on Microeconomics
• The impact of behaviour on businesses
• Utility maximisation and consumer demand estimation​
• Profit maximisation and production function estimation​
• Market failures, externalities and empirical evaluation of regulation​

Module 5: Hypothesis Testing

• Empirical formula
• Concepts and skills for hypothesis formulation
• Setting the stage
• Hypothesis testing
• Statistical software
• Mathematical theories
• Statistical theories for economics
• Stata software
• Point estimation and properties of estimators (unbiasedness, consistency, efficiency)​
• Confidence intervals and p-values in regression analysis​
• Model specification tests and goodness-of-fit measures​

Module 6: Econometrics

• Advanced Theories of Econometrics
• Variable models
• Instrumental variables
• Using quasi-experimental data
• Sample selection
• Fixed effects
• Censoring of samples
• Limited dependent variables model
• Panel methods
• Time-series techniques, in general
• Simultaneous equations in economics
• Maximum likelihood estimation and its applications​
• Ridge and lasso regression for handling multicollinearity and high-dimensional data​
• Binary choice models (logit, probit) and binary classification​
• Dynamic models in economics, including distributed lag and VAR models​
• Difference-in-differences and matching methods for causal inference​

Module 7: Surveying of Economic Development

• Modern theories
• Applications of economic techniques
• Evolution of economics
• Determining economic development
• Development issues and challenges
• Important issues in economic development
• Use of development indicators such as HDI, poverty and inequality measures​
• Impact evaluation of development programmes using econometric methods​
• Role of institutions and governance in economic development​

Module 8: Econometrics for the Public

• Political economy
• Financing of government interventions
• Concepts of market equilibrium
• Economy of voting
• Public sector programmes
• Deficit financing
• The efficiency of the market
• Government intervention through taxation
• Departures from efficiency
• Rent-seeking
• Financing the government
• Empirical analysis of tax incidence and redistribution​
• Estimating the effects of public spending programmes on outcomes​
• Voting behaviour models and empirical political economy​

Module 9: Gaining Economic Stability

• Financial system’s contributions towards the growth
• Microeconomic and Macroeconomics of financing growth and Stability
• Regulatory issues
• Causes, impact, and Consequences of the Crisis
• Concentration and competition
• Determinants of bank efficiency and Competition
• “Too Big to Fail” debates
• Macroprudential policy issues
• Determinants of stability or instability of the economy
• Product of economic growth
• Lender of last resort
• Deposit insurance
• Systemic risk measurement using market and balance-sheet data​
• Stress-testing frameworks and scenario analysis for financial stability​
• Evaluating the impact of macroprudential tools with panel and time-series models

Training Impact

The impact of Applied Econometrics training is visible in how organizations achieve stronger evidence-based policy and strategy, more robust financial risk management in large banks, and better design of novel public-health and pricing policies.​

University of Sheffield – Alcohol Pricing and Health Impacts Through the Sheffield Alcohol Policy Model

Implementation: The University of Sheffield’s Sheffield team developed the Sheffield Alcohol Policy Model for the UK Department of Health, combining an econometric price-to-consumption module with an epidemiological consumption-to-harm module to project the effects of policies like minimum unit pricing on hospital admissions, crime, and mortality. The Sheffield model was originally commissioned by the UK government’s Department of Health to model the impact in health, crime and economic terms of a number of different policy options including a ban on below-cost sales, a ban on off-sales promotions, increases in alcohol duty and MUP (with a range of different levels for the price per unit considered). The econometric component (referred to as the ‘price-to-consumption’ model) relates policy interventions to price changes and hence consumption changes by calculating ‘elasticities’, which measure how purchasing of a product changes in response to a price change, with the model operating in a sophisticated manner by allowing for considerable heterogeneity in responses to policy interventions. This includes allowing for responses to differ by population subgroups (e.g. by age, gender and drinker type, i.e. moderate, hazardous or harmful consumption and ‘binge’ drinker status) and different alcoholic products (e.g. beer, wine, spirits and alcopops), with the population subgroups chosen in conjunction with policymakers to allow the modelling of effects on specific groups of interest, such as young ‘binge’ drinkers who have been considered a policy priority within the UK government. The epidemiological component (also referred to as the ‘consumption-to-harm’ model) takes these estimated consumption changes and relates them to outcomes of interest (e.g. hospital admissions, crimes, mortality) in a deterministic manner based on population attributable fractions.​

Results: The model estimated, for instance, that setting MUP at 50 pence per unit would reduce consumption by 5.7% and 8600 hospital admissions per year, and these figures became central to public and parliamentary debates, exemplifying the type of policy-relevant modeling techniques taught in this course. Results of the Sheffield model have been highly influential in the policy debate, with the model helping those advocating for policy change by demonstrating that the introduction of a MUP is likely to be a more targeted intervention than other policy options (such as increasing alcohol duty), with those who drink hazardously and harmfully most likely to consume cheaper alcohol and are therefore affected by the policy to a greater extent than those who drink moderately. Thirty-six one-to-one semi-structured interviews were conducted with individuals who had been directly involved in the UK- and/or Scotland-based policy debates on MUP, with participants purposively chosen to create a diverse sample including politicians, civil servants, academics, advocates and industry-related actors. Interviewees felt familiar with modelling studies and often displayed detailed understandings of the Sheffield model, with respondents typically showing a high level of knowledge about the results and methodology of the Sheffield model, with one politician accurately committing detailed figures from the Sheffield model to memory during verbal discussion. There was general enthusiasm for increased use of econometric modelling to inform future policymaking but an appreciation that such evidence should only form one input into the process.​

Large U.S. Investment Bank Holding Company – CCAR Stress-Testing with Econometric Loss Models

Implementation: A case study on the equity portfolio of a U.S. investment bank holding company explains how the firm built econometric models to forecast nine-quarter losses under different macroeconomic scenarios to satisfy the Federal Reserve’s CCAR requirements. An annual exercise conducted by the Federal Reserve to assess whether the largest bank holding companies operating in the United States have sufficient capital to continue operations throughout times of economic and financial stress, CCAR is applicable for large banks with total consolidated assets greater than 50 billion USD, with outlier banks facing ban on capital distribution, severe penalties and operational restrictions. Large bank holding companies need to develop forward-looking econometric models to forecast revenues, losses and balances, demonstrating sufficient capital to absorb losses and support operations during supervisory scenarios. The development process involved discussion with stakeholders to define the problem statement, identifying raw data sources, analyzing and cleansing and aggregating data, specifying model framework, iterative variable selection and segmentation, followed by performance testing, statistical testing, stress testing and sensitivity analysis, independent model validation, and ongoing model risk management. The model used multiple linear regression with log transformation with the equation: EquityPortfolio = α + β₁ln(CRE) + β₂ln(BBBCorpYield) + ε, calibrated using ordinary least squares, with statistical testing including stationarity tests (Phillips Peron and ADF), linearity test (Ramsay-Reset), multicollinearity (Variable Inflation Factor), normality tests (Jarque-Bera, Shapiro Wilk), heteroskedasticity tests (Breusch Pagan), and serial-correlation tests (Durbin-Watson, Breusch-Godfrey).​

Results: Because outlier banks risk bans on capital distributions, severe penalties, and operational restrictions, the quality of these econometric stress-testing models directly affects strategic decisions about lending, capital buffers, and shareholder payouts exactly the kind of high-impact, data-driven work for which this applied econometrics course prepares participants. The model demonstrated strong in-sample performance with RMSE of 4.8 million and MAPE of 3.70%, and out-of-sample performance with RMSE of 9.75 million and MAPE of 6.32%. Under supervisory stressed scenarios, Commercial Real Estate tends to be significantly lower under severely adverse scenarios while BBB corporate yields tend to be significantly higher under severely adverse scenarios, with the model generating economically intuitive stress forecasts across baseline, adverse, and severely adverse scenarios. Expected 13-quarter loss under baseline scenario was 5.18 million, under adverse scenario was 8.78 million, and under severely adverse scenario was 17.63 million from an initial portfolio value of 273.35 million in Q4 2017. Key takeaways include forward-looking capital plans enabling stress testing balance sheet and P&L statements, intuitive risk analysis with economic intuition driven models and output, regulatory compliance meeting new forward-looking regulations like CCAR, IFRS 9, FRTB, and IRRBB, and actuaries’ skillset being compatible with econometric modelling combining statistics, business, finance and economics.​

Minimum Wage and Education – Econometric Evidence for Labour and Education Policy

Implementation: Applied econometrics case studies describe how economists use large datasets and regression models to estimate the effect of minimum wage laws on employment and the impact of education on earnings. One example of applied econometrics is the study of the impact of minimum wage laws on employment, with economists using econometric methods to analyze data on wages and employment levels to estimate the effect of changes in minimum wage laws on job creation and unemployment rates. By using regression analysis and other econometric techniques, economists are able to quantify the relationship between minimum wage increases and changes in employment levels, providing valuable insights for policymakers and businesses. Another example is the analysis of the relationship between education and earnings, with econometric methods used to estimate the effect of education on individuals’ earnings by analyzing data on educational attainment and income levels. By controlling for other factors that may influence earnings, such as work experience and skills, economists are able to measure the impact of education on individuals’ earning potential.​

Results: For example, researchers study changes in minimum wages across regions and over time to see how low-wage job numbers respond, and they use micro data on individuals’ schooling, experience, and wages to separate the “return to education” from other factors results that ministries of labour, education departments, and employers use when setting wage floors or designing education funding. This type of analysis provides important information for policymakers and educators about the economic benefits of investing in education. Econometric methods are widely used to evaluate the impact of economic policies on various outcomes, such as employment, inflation, and economic growth, with economists using econometric models to assess the effectiveness of monetary policy in controlling inflation by analyzing the relationship between changes in interest rates and changes in consumer prices. By using time series data and statistical techniques, economists are able to estimate the impact of monetary policy on inflation rates and provide valuable insights for central banks and policymakers. Examples of applied econometrics in practice include studies on the impact of minimum wage laws on employment, the effectiveness of monetary policy in controlling inflation, the relationship between education and earnings, and the evaluation of the impact of trade agreements on economic growth, all using econometric methods to analyze real-world data and draw conclusions about economic relationships and policy implications.​

Be inspired by how applied econometrics shapes public policy, financial risk decisions, and labor market reforms. Join the Rcademy Applied Econometrics Training Course to gain the quantitative skills that support evidence-based policy and strategy.