Mid-Year Economic Outlook: Navigating Stagflation Risks & Shifting Consumer Priorities

With inflation lingering, interest rates holding, and consumers pulling back, the second half of 2025 is shaping up to be anything but predictable. For suppliers and brands, rising tariffs, mounting debt, and shifting fiscal policies are introducing new challenges – and changing the way shoppers engage, spend, and trade down.

Join CRC’s Skylar Xie and Qi Zhang on Thursday, July 17 for our 2025 Mid-Year Economic Outlook Webinar. This 60-minute session will provide a timely update on the macroeconomic landscape and what it means for your business.

We’ll cover:

Tariffs: Inflation pressures and trade policy developments with major partners
Government Policy: Economic impact of immigration, tax, and fiscal spending updates
Consumer Spending: Financial strain, rising debt, and shifting purchasing behaviors
Outlook Update: Macroeconomic headline indicators and industry channel performance

Save your seat to better position your business for the second half of the year and beyond.

Registrants will receive the slide deck and audio replay following the call.

About the Presenter

Skylar Xie, CFA

Director, Macro Research

Cleveland Research Company

Skylar is the Director of Macro Research at Cleveland Research Company. She was one of the founders of CRC’s Macro Insights, connecting the dots between CRC’s bottoms-up channel research and top-down economic data.

Skylar holds a Bachelor’s Degree in Economics from Beijing Jiaotong University in Beijing, China. She also holds a Master of Science in Finance and graduated with Dean’s Academic Reward from Case Western Reserve University in Cleveland, Ohio. In May 2021, Skylar received her MBA from the Wharton Business School in Philadelphia, PA and is a CFA® charterholder.

Qi Zhang

Senior Macro Associate

Cleveland Research Company

Qi Zhang is the Senior Macro Associate at Cleveland Research Company. Over the past 6 years, she developed strong skillsets in building and improving forecasting models of macro-economic factors (for example, headline consumer spending, consumer inflation growth) using advanced machine learning techniques.

She has experience in connecting industry-specific data using macro-economic factors, and has industry knowledge in the consumer sector. For instance, she developed forecasting models of retail sales growth by end market, using her knowledge of key statistical approaches like ARIMA (AutoRegressive Integrated Moving Average), and machine learning models including random forest, XGBoost, etc.