以下是中文翻译： 凯文·帕弗拉斯（Kevin Paffrath）是一家房地产公司的首席执行官，他对华盛顿特区的房地产市场进行了分析，起因是有人声称该市场房价下跌了8.6%，并将其归因于“狗狗币”（doge，此处可能指的是埃隆·马斯克在某个政府机构的影响力）引发的裁员。帕弗拉斯批判性地审查了这些数据，将它们与更广泛的房地产趋势进行了对比，并警告人们不要草率下结论。 帕弗拉斯首先驳斥了房价崩溃的说法，强调房地产市场中，逐月比较中间销售价格通常具有误导性。这是因为每月数据中，不同类型的房产（公寓、联排别墅、独栋住宅）组合各异，且样本规模相对较小。他认为，小幅波动可能会被夸大，扭曲中位数，并造成一种虚假的波动感。为了正确理解市场，需要一个更长期的视角，例如使用移动平均线来分析多年的趋势。 他引入了“新冠泡沫”及其随后的“新冠反转”的概念。在疫情期间，许多人从加州等高成本地区搬迁到德州和佛罗里达州等地区。随着这些市场出现过度建设，且人们现在开始回流，反转正在发生。帕弗拉斯指出，他的房地产公司预见到了这种反转，并战略性地投资于加州等地区，因为那里严格的建筑法规和高需求限制了供应。 回到华盛顿特区市场，帕弗拉斯认为自新冠疫情以来，该市场一直相对平稳。他将华盛顿特区的表现与佛罗里达州坦帕市（新冠疫情繁荣的受益者）和德克萨斯州奥斯汀市（经历了更快的反转）的表现进行了比较。坦帕的房屋价值大幅增长，而奥斯汀则更早达到顶峰，此后有所下降，而华盛顿特区则在相对稳定的12万美元价格范围内波动。 为了更深入地分析华盛顿特区的市场，帕弗拉斯使用了Redfin的数据中心，选择了中间销售价格的4周和12周移动平均线。与房价崩溃的说法相反，他发现华盛顿特区的房屋价值实际上同比上涨了2%（4周移动平均值）和3%（12周移动平均值），高于往年。他还将华盛顿特区的失业率与往年进行了比较，发现它处于正常水平。 帕弗拉斯承认裁员的逻辑影响，即失业对住房的影响。然而，他告诫人们不要妄下结论。他承认活跃房源数量有所增加，但活跃月份的供应量仍然稳定，这说明该地区的买家需求依然存在。他还指出房价下降幅度有所增加，但同时也指出现在才年初，而且仅比2024年高出0.9%。 然后，他指出了加州房地产的细微之处。他挑战了普遍认为加州严格的法规和高成本是有害的观点。矛盾的是，他解释说，它们正是推动房地产价值上涨的因素。该州的缓慢增长政策限制了建筑，从而限制了供应，并由于其就业市场和理想的气候而推高了需求。他用德克萨斯州为例，该州的限制较少，可以轻松增加住房供应并因替代效应而降低单个房屋的价值。 总而言之，凯文·帕弗拉斯使用移动平均线来反驳关于华盛顿特区房地产市场因裁员而崩溃的说法，他认为数据显示，从长远来看，华盛顿特区的房屋价值实际上是稳定的。他提倡一种全面且知情的房地产分析方法，强调长期数据、移动平均线和实地研究的重要性。

Kevin Paffrath, CEO of a real estate company, delivers an analysis of the Washington D.C. real estate market, spurred by claims of an 8.6% price decline allegedly tied to layoffs initiated by "doge" (presumably referring to Elon Musk's influence at a government agency). Paffrath critically examines the data, contrasting it with broader real estate trends and cautions against drawing hasty conclusions. Paffrath begins by addressing the immediate claim of a price collapse, emphasizing that month-over-month comparisons of median sales prices in real estate are often misleading. This is due to the varied mix of properties (condos, townhomes, single-family homes) and relatively small sample sizes in monthly data. He argues that small fluctuations can be exaggerated, skewing the median and creating a false sense of volatility. To properly understand the market, a longer-term perspective is needed, such as analyzing trends over several years using moving averages. He introduces the concept of the "COVID bubble" and its subsequent "COVID reversal." During the pandemic, many people relocated from high-cost areas like California to regions like Texas and Florida. As these markets experienced overbuilding, and people are now returning, a reversal is occurring. Paffrath notes that his real estate company anticipated this reversal, strategically investing in areas like California, where strict building regulations and desirability limit supply. Transitioning back to the D.C. market, Paffrath argues that it has remained relatively flat since COVID. He compares D.C.'s performance to that of Tampa, Florida (a COVID boom recipient) and Austin, Texas (which experienced a faster reversal). While Tampa saw substantial housing value growth, Austin peaked earlier and has since declined, while D.C. has bounced in a relatively stable 120,000 price range. To analyze D.C.'s market more thoroughly, Paffrath uses Redfin's data center, opting for 4-week and 12-week moving averages of median sales prices. Contrary to the claims of a collapse, he finds that home values in D.C. are actually up 2% year-over-year (4 week avg) and 3% year-over-year (12 week avg), higher than in previous years. He also compares D.C's unemployment to prior year and finds it is normal. Paffrath addresses the layoffs, acknowledging the logical impact of unemployment on housing. However, he cautions against jumping to conclusions. He acknowledges active listings are up, yet active months of supply remains stable which accounts for buyer demand in the area. He also addresses higher price drops, but also notes that we’re at the beginning of the year, and that it’s only .9% over 2024. He then points to the nuances of California real estate. He challenges the common perception that California's stringent regulations and high costs are detrimental. Paradoxically, he explains, they are the very factors that drive up property values. The state's slow-growth policies restrict building, thereby limiting supply and driving up demand due to its job market and desirable climate. He uses the analogy that Texas, with less restrictive regulations, can easily increase the housing supply and decrease individual home value due to substitution. In conclusion, Kevin Paffrath uses moving averages to dispute the claim that the Washington D.C. real estate market is collapsing due to layoffs, arguing that the data actually show that home values in D.C. are stable in the long-term. He advocates for a comprehensive and informed approach to real estate analysis, emphasizing the importance of long-term data, moving averages, and on-the-ground research.