Econometric modelling & data analytics

Our team has a broad range of econometric and data analytics expertise that we use to help our clients answer important questions. We generate leading insights from our analysis to support governments, regulatory bodies and firms in their strategic decisions.

We follow these key principles:

  • Ensure our processes are transparent, flexible and robust
  • Use cutting-edge modelling techniques
  • Combine industry expertise through PwC’s global network

We have specialist capabilities in the following areas:

Forecasting

The future is never certain; using advanced econometric methods, we can pick up trends and signals and make projections of likely future scenarios that help answer your business questions.

Key questions we can help clients to answer:

  • Forecasting demand: What will energy demand look like in the future? How will future postal volumes change given developments in e-commerce? How do you forecast passenger demand in the transport sectors?
  • Macroeconomic forecasting: What are the short-term (<1 year), medium-term (1-5 years) and long-term (>5 years) projections for key macroeconomic variables such as GDP, inflation, and house prices? How will these impact my business?
  • Revenue and price forecasting: How do competitors’ pricing decisions affect our revenues? How do we set prices that maximise our profits?

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Benchmarking and efficiency analysis

Using advanced econometric analysis such as Stochastic Frontier Analysis (SFA), we help businesses and regulators to identify more efficient entities after accounting for variables that are outside of management’s control.

Key questions we can help clients to answer:

  • Cost efficiency analysis: What is the efficient level of costs for a company? What are the key drivers of cost? How do efficiency levels of business units compare within a company?
  • Production efficiency analysis: What is the efficient level of production for a company?

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Causal impact assessment and appraisal

We apply a wide array of econometric and economic modelling methods, such as Computable General Equilibrium (CGE) and Granger causality tests, to assess impacts of policies and infrastructure investments under different options.

Key questions we can help clients to answer:

  • Government policy options appraisal: How might a policy impact the economy, businesses, society and the environment? Which is the best policy option?
  • Investment options appraisal: What are the economic and revenue impacts of my investment options?
  • Causal study designs for quantifying effects from products: How effective are our financial products in helping businesses grow?
  • Causal study designs for quantifying effects from government programmes: What is the net effect of a policy intervention? How successful are trade promotion activities? How impactful are certain international aid programmes?

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Large scale data modelling and analysis

We use big data methods to draw business insights from large datasets that you already have.

Key questions we can help clients to answer:

  • Large scale hypothesis testing: How can I reliably test a large number of hypotheses in my data?
  • Machine learning for complex relationships and prediction: How can I understand more complex relationships in my data and more accurately predict outcomes?
  • ‘Big data’ analysis of surveys: How can I process and use big data (for example from large surveys) to answer key questions?

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Marketing effectiveness measurement

The marketing media landscape is continuously changing. Using your own sales and marketing data, we help you determine the optimal marketing mix to maximise return on investment.

Key questions we can help clients to answer:

  • How do different marketing channels contribute to sales over time?
  • What is the optimal mix across marketing channels to optimise return on investment, in both short and long term?
  • How do my sponsorship arrangements affect sales and return on investment?

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Price elasticity and demand modelling

Using your sales data and our access to bespoke market databases, we can help you to understand the drivers of demand for your products and how you can optimise your pricing decisions going forward.

Key questions we can help clients to answer:

  • Drivers analysis: What are the key drivers of demand? How does competitor pricing impact demand for our services?
  • Pricing analysis: What is the price elasticity of demand for our products? What is the optimal level of pricing? How does price elasticity of demand change over time?

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Case studies

House price forecasting

How do you build a robust long term forecasting model to inform your commercial strategy? This was the exam question asked by a UK financial services group. We helped our client build an econometric model to forecast house prices over the next fifty years using our expertise in machine learning and Monte-Carlo simulation.

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Mixed marketing modelling (MMM) for maximum marketing effectiveness

We recently supported a major airline assess their return on investment from historical marketing expenditure and helped them optimize their strategy going forward.

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Impact Assessment of Growth Capital Lending

We assisted Santander in quantifying the impact of their growth capital lending on SMEs. We looked at the impact on revenue, profit and employment using a machine learning based propensity score model and distance-based methods.

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Contact us

Jonathan Gillham

Jonathan Gillham

Chief Economist, PwC United Kingdom

Tel: +44 (0)7714 567297

Edmond Lee

Edmond Lee

Senior Economist, PwC United Kingdom

Tel: +44 (0)7802 660423

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