https://keeganstimeseries.com/tag/microeconomics/ Microeconomics Hugo Blox Builder (https://hugoblox.com)en-usMon, 02 Nov 2026 00:00:00 +0000 https://keeganstimeseries.com/media/icon_hucb5343885e062dfd39f0924c6a9ba323_52880_512x512_fill_lanczos_center_3.png https://keeganstimeseries.com/tag/microeconomics/ https://keeganstimeseries.com/project/enterprise-workforce/ Mon, 02 Nov 2026 00:00:00 +0000 https://keeganstimeseries.com/project/enterprise-workforce/ <h2 id="a-deliberately-separate-firm-level-model">A deliberately separate firm-level model</h2> <p>Economy-wide labor statistics describe the aggregate outcome of decisions, while enterprise systems record the administrative details of employment relationships. This project uses <strong>synthetic enterprise records</strong>, not confidential employer data, to demonstrate how those details can be modeled.</p> <h2 id="enterprise-semantic-model">Enterprise semantic model</h2> <figure class="owas-portfolio-figure" style="margin: 1.75rem auto 2rem; max-width: 1020px;"> <a href="https://keeganstimeseries.com/images/owas/enterprise-semantic-model.webp" target="_blank" rel="noopener"> <img src="https://keeganstimeseries.com/images/owas/enterprise-semantic-model.webp" alt="Power BI model diagram with person, job, organization, and date dimensions alongside assignment history, month-end headcount, employment spells, compensation events, leave episodes, and recruiting applications." loading="lazy" decoding="async" style="display:block;width:100%;height:auto;border:1px solid #ddd;border-radius:8px;box-shadow:0 8px 25px rgba(0,0,0,.10);" /> </a> <figcaption style="font-size:.9rem;line-height:1.55;margin-top:.6rem;color:#586174;">Synthetic enterprise Power BI model (development snapshot). Dimensions and event/snapshot facts remain separate to preserve their distinct grains. Some date relationships are inactive and must be addressed deliberately in measures.</figcaption> </figure> <p>The model distinguishes <strong>people, employment spells, assignments, time-bound snapshots, compensation events, leave episodes, and applications</strong>. These entities represent different analytical units and should not be merged into a single generic employee table.</p> <p>The diagram includes:</p> <ul> <li>Dimensions for person, job, organization, and date.</li> <li>Employment spell, assignment history, and workforce month-end facts.</li> <li>Compensation events, leave episodes, and recruiting applications.</li> <li>DAX measures for headcount, hires, separations, and workforce reconciliation.</li> </ul> <h2 id="analytical-questions">Analytical questions</h2> <p>How sensitive is turnover to the selected separation events and denominator? How do month-end counts differ from exposure-based measures? What changes when a model uses employment spells and time-varying covariates rather than a one-row-per-person extract?</p> <h2 id="modeling-roadmap">Modeling roadmap</h2> <p>The synthetic dataset is intended to support reproducible data-quality tests, descriptive dashboards, survival modeling, and predictive diagnostics. Any reported model performance will require actual fitted results and documented validation.</p> <p><strong>Status:</strong> Architecture under development. The diagram demonstrates structure; it does not claim deployed forecasting or prediction performance.</p>