Business Cycle Evaluations

***Synchronization of endogenous business cycles***   A debate that is almost as old as economics itself is what recessions and booms originate from. Are they driven by events external to the economy, like natural disasters, or by forces internal to the economy, such as debt accumulation? In my recent paper published in the Journal of Economic Behavior and Organization, I tackle this question indirectly by examining the synchronization of economic activity across countries. The findings suggest that both external and internal forces are needed to explain empirical data.   Some terminology first. Business cycles. Sequences of booms and busts in economic activity. Exogenous business cycles. Driven by external “shocks”. Mathematically, the economy is described by a stable steady state buffeted by shocks. Endogenous business cycles. Driven by forces internal to the economy. Mathematically, the economy follows non-linear dynamics, such as limit cycles or chaos. Comovement. Positive correlation of economic activity. Synchronization. Alignment of non-linear dynamics.   It’s very hard to distinguish between exogenous and endogenous business cycles directly looking at time series of economic activity, partly because we have data for only ~10 cycles. It helps to look at properties of the economy for which exogenous and endogenous theories make different predictions. Here, I consider comovement of economic activity across countries. If business cycles are exogenous, comovement comes from shock propagation. If business cycles are endogenous, countries would follow non-linear dynamics in isolation, while linkages lead to *synchronization*. In the paper I quantify these effects through a very simple 2-equation model that describes business cycles in countries connected through international trade. When business cycles are exogenous, comovement is too low compared to the data; when they are endogenous, it is too high. The right combination of endogenous and exogenous cycles instead matches the data.   Thus, although the currently dominant view is that business cycles are exogenous, this paper provides a new type of evidence that they are at least in part endogenous. Although I’m not the first having this idea, this is the first paper that provides a complete mathematical theory and quantitative test. If the main result holds in more complex models, evidence on endogenous business cycles will have important implications in macroeconomic forecasting and policy making.   This contribution, which happens to be my only single-authored paper, comes from the last chapter of my PhD thesis, and took so long mostly because I had no coauthors nagging me to finish the paper 😊 I’m glad I could publish it in the JEBO special issue on complexity economics that I’m co-editing (all editor papers went through the editor-in-chief of the journal to avoid conflicts of interest).   Link to the paper (free access until January 18): https://lnkd.in/dwYJFSuf

🔍 𝗗𝗼 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄 𝘄𝗵𝗮𝘁 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐂𝐲𝐜𝐥𝐞 𝐀𝐜𝐜𝐨𝐮𝐧𝐭𝐢𝐧𝐠 (𝐁𝐂𝐀) 𝗶𝘀 — 𝗮𝗻𝗱 𝘄𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀? In short: BCA is a powerful framework for analyzing macroeconomic fluctuations by decomposing them into a set of “wedges” — e.g. efficiency, labor, investment, and government consumption distortions — that help us understand which frictions or shocks are driving business cycle dynamics. Since its introduction (Chari, Kehoe & McGrattan, 2007), it has been applied across many countries and recessions to guide theory development by identifying the key mechanisms behind economic fluctuations. 📝 Want to know more? Read my survey paper Business Cycle Accounting: What Have We Learned So Far? ➤ Link: https://lnkd.in/gEWQXSie 📝 𝗧𝐰𝐨 𝐫𝐞𝐜𝐞𝐧𝐭 𝐚𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 𝐈’𝐝 𝐥𝐢𝐤𝐞 𝐭𝐨 𝐬𝐡𝐚𝐫𝐞 Accounting for Mexican Business Cycles — we apply BCA to Mexico’s major crises (1995 and 2008) and show that the efficiency wedge is the dominant driver. ➤ Link: https://lnkd.in/duxmTmSK The Covid-19 Recession in Germany: A Macro-Epidemiological Analysis — we investigate how pandemic-related containment policies shaped output fluctuations during COVID-19, showing that consumption and labor-supply responses account for almost all weekly GDP dynamics, and that policy interventions played a crucial role in determining the depth and trajectory of the recession. ➤ Link: https://lnkd.in/d-V46Qkp ✅ Why this matters — for researchers, policymakers, and practitioners BCA acts as a compass for researchers: by identifying which wedges are “active,” it helps narrow the space of promising theoretical models. In applied work, it can reveal whether productivity shocks, labor distortions, or financial frictions are more relevant. 📣 If you’re curious about: - how to implement BCA in your own country or dataset - the limitations, caveats, and extensions of the method - the economic interpretation of particular wedges - or applications to emerging markets … I’d love to connect. You can also check the full survey or the country-specific applications above as starting points.

Excellent news for the economics community! It is with great pleasure that I share an important update for those engaged in macroeconomic analysis of the euro area. As of 2025, the Euro Area Business Cycle Network (EABCN) has taken over responsibility for updating the Area-Wide Model (AWM) database, originally developed and maintained by the European Central Bank. By way of background: the AWM was, for many years, a key reference for macroeconomic modelling of the euro area. Although the ECB officially decommissioned the model in 2010, the data continued to be made available until 2019 and remained a valuable resource for empirical research. Since then, many of us have felt the absence of systematic updates to this dataset, which is crucial for analysis of the business cycle, output gap estimation, and broader macroeconomic dynamics within the monetary union. The EABCN’s decision — through its Business Cycle Dating Committee, to resume and maintain updates to this database constitutes a significant service to the profession. It not only ensures continuity in empirical research based on a consistent historical dataset, but also strengthens our capacity to assess the cyclical position of the euro area economy using reliable tools. One might ask: does this initiative signal a renewed interest in medium-term modelling frameworks for the euro area? Are academics and policymakers ready to reappraise analytical instruments that, while classic, continue to offer predictive and interpretative value? Regardless of the answer, this is a wise revival of a data infrastructure with tangible impact on applied economic analysis. The updated database is now accessible to the entire academic and professional community, an opportunity I strongly encourage colleagues to take advantage of. #Database in: https://lnkd.in/dsGK8Sax

📊 CMA 107 — Aligning Working Capital with the Business Cycle A flat working capital projection is like wearing the same clothes all year — it ignores the weather. Yet, many CMA reports show: Stock: ₹1.5 Cr Debtors: ₹2.0 Cr Creditors: ₹1.0 Cr — same across all quarters. 🔍 Why It Matters If you show steady WC, the banker assumes your business is stable month-on-month. But if: • You’re a festive-season manufacturer, stock builds up in Q2 • You’re in agri or infra, Q1 and Q3 might be monsoon-slow • You get customer advances, WC need may be lower early on, higher post-dispatch Then your real cycle is being under-appraised — or worse, over-financed in the wrong quarter. ⸻ ✅ What to Show in CMA Data: 1. Quarter-wise Movement of Current Assets & Liabilities • Build stock in the quarter before peak sales • Let debtors build after dispatch • Adjust creditors based on vendor terms — don’t just plug 90 days blindly 2. Receivables and Payables Based on Actual Collection Patterns • If your actual realization is 60–75 days, don’t assume 30 days in projections • Show staggered inflow, especially if project-based or milestone-linked 3. Link Operating Cycle to Sales/Production Volume • Higher sales = higher WC need • If a plant is down in Q2, show reduction in RM and WIP ⸻ 🧠 Credit Insight: A CMA that mimics your operational rhythm is far more creditworthy than one that just “balances out.” It helps the banker: • Assess peak WC gap • Plan disbursements better • Trust your numbers ⸻ 🔎 Pro Tip: Always link: Projected Sales ⟶ Inventory buildup ⟶ Debtor movement ⟶ Creditors ⟶ WC requirement ⸻ 📎 Up Next: CMA 108 — Capex & Depreciation: When Numbers Don’t Talk to Each Other #CMA107 #WorkingCapital #BusinessCycle #SeasonalityMatters #BankFinance #CMAAnalysis #LinkedInFinance #CreditAppraisalSeries

Canadian GDP has now contracted for two consecutive quarters, and the “R-word” is making the rounds again. A primer I wrote a few years ago remains a useful reminder that defining a recession in Canada isn’t as straightforward as the “two consecutive quarters of negative GDP” rule of thumb. In Canada, recession is determined by the Business Cycle Council at the C.D. Howe Institute, which evaluates economic downturns through three lenses: duration, amplitude, and scope. Its definition of a recession is “a pronounced, persistent, and pervasive decline in aggregate economic activity.” That means even a single quarter of negative GDP growth could ultimately be judged a recession if weakness persists and becomes broad-based. Conversely, two quarters of contraction do not automatically qualify. The last time the Council weighed in on the issue, in September 2025, it concluded that the economy had not met the threshold for a recession despite quarterly declines in GDP. Today, #cdnecon is clearly operating below capacity, which is not surprising given the uncertainty surrounding CUSMA negotiations and broader trade tensions. The weakness is most evident in trade-exposed industries. At the same time, domestic demand has remained relatively resilient, suggesting the story is more nuanced than the headline GDP figures imply. For anyone interested, here’s a short primer on how recessions are actually determined in Canada and the U.S.⬇️ https://lnkd.in/e2u46zt7 Version française ⬇️: https://lnkd.in/eyTUkbWW

Business ups and downs are inevitable. Many people call them “luck” or “market mood,” but in reality, they’re part of the Business Cycle. Every business goes through phases.When growth comes, it eventually slows. And when times get tough, the same business can rise again with smart planning. This cycle affects every business clothing brands, service-based companies, and physical stores alike. The four phases are: Expansion, Peak, Recession, and Recovery. In Expansion, demand is high and customers spend easily yet this is where many businesses overspend instead of strengthening cash flow. The Peak phase looks perfect but is the most dangerous. No savings, only luxury products, or a narrow customer funnel can make sales crash when the market turns. Recession reveals true business strength. Customers spend only on essentials. Brands with strategy, mid-range offerings, strong loyalty, and relationship-based marketing survive. Recovery comes slowly and demands patience. The smart move is to apply lessons learned, use data, and invest only where productivity grows. To stay prepared: ✔ Save in Expansion ✔ Fix systems in Recession ✔ Apply lessons in Recovery ✔ Build funnels for multiple income levels Data, planning, and market awareness drive long-term success. Stay safe, Sidra Naseem Digital Marketing Trainer | Entrepreneur | Business Consultant #SidraNaseem #BusinessCycle #BusinessPlanning #SmartEntrepreneur #NoMoreGuesswork