The amazing Pinchas Zukerman, Amanda Forsyth and Michael Stephen Brown brings a night of exquisite classic trios to the well-educated-but-enthusiastically-clapping-between-mvts Chicago audience on a cozy Saturday night. Mendelssohn Piano Trio No. 1 Higdon Pale Yellow from Piano Trio Dvořák Dumky for Piano, Violin and Cello, Op. 90 The music moved me. And the program is nice — just pure beauty, elegance and joy, no need for an avant garde piece to prove anything this time. ...

A bee does not waste its energy trying to convince a fly that honey is better than shit. During award season, the movie star Tim Cha commented on ballet and opera that it’s “barely alive” and “no one cares about it anymore”. He made a big point, and got blackslashed by all major opera houses. The Seattle opera even released a TIMOTHEE discount code for 14% off. It’s interesting to debate the future of the classical art industry, but certainly not during award season. ...

The CSO curates program with glittering wisdom. A while ago back in November, Robert Chen led the strings to present Vivaldi’s Four Seasons, the winter was shapr and cold. And now, our new artistic director led an adorable (and impressive) program welcoming spring: Milhaud Le Bœuf sur le toit Gershwin An American in Paris Stravinsky The Rite of Spring Klaus Mäkelä conducted CSO March 5, 2026. Two nearly sold out nights. The concert program is nice and covers stories about the music: https://issuu.com/chicagosymphony/docs/program_book_-_m_kel_conducts_the_rite_of_spring ...

Motivation In the standard neoclassical model, three return measures coincide: $$ R^{rf} = \mathbb{E}R^k_{t+1} = MPK. $$ This is a strong and testable prediction. Empirically, all three diverge and move differently over time. The question is: what drives the wedges? The answer: risk drives a wedge between $R^{rf}$ and $\mathbb{E}R^k$; markups drive a wedge between $\mathbb{E}R^k$ and $MPK$. Model A representative household with CRRA preferences $\mathbb{E}_0\sum_t \beta^t \frac{C_t^{1-\sigma}}{1-\sigma}$, inelastic labor supply $\bar N$. ...

We will analyze a representative agent economy and see how shocks and intertemporal discounted tradeoff drives asset prices. Stochastic Environment Primitives. Time is discrete, $t = 0, 1, 2, \ldots$ A random variable $s_t$ (the “state”) summarizes all exogenous shocks at date $t$. The initial state $s_0$ is known. Histories. A history of shocks through date $t$ is the tuple $$s^t = (s_0, s_1, \ldots, s_t).$$We write $s^{t+1} \geq s^t$ to mean that $s^t$ is a prefix of $s^{t+1}$ (i.e., the first $t+1$ entries of $s^{t+1}$ coincide with $s^t$). ...

Finally! Let’s talk about shocks. Motivation U.S. per capita real GDP (in logs) exhibits a clear upward trend over the 20th century. The neoclassical growth model explains this trend well. However, GDP also fluctuates around this trend. The question is: can the same neoclassical framework, driven solely by productivity shocks, also explain these cyclical fluctuations? To isolate cycles, we decompose log GDP into a trend component (extracted via the Hodgkin–Prescott filter or a band-pass filter) and a cyclical component (the residual). The cyclical component reveals the following stylized facts from U.S. quarterly data (1947–1995, HP-filtered): ...

Lecture 9 measures misallocation but under a simple market structure (intermediate firms -> final firms -> production). Baqaee and Farhi (2020) extended the analysis to arbitrary production network. With general CRS technology assumption, one can decompose GDP growth into contributions from technology, factor accumulation, and misallocation—all using observable data. Environment Primitives There are three classes of agents: $N$ producers (firms), indexed $i = 1, \dots, N$. $F$ primary factors, indexed $f = 1, \dots, F$, supplied inelastically in quantities $\bar{L}_f > 0$ (exogenous). A representative consumer and a final good sector. The exogenous objects are: productivities $\{A_i\}_{i=1}^N$, factor endowments $\{\bar{L}_f\}_{f=1}^F$, and functional forms $\{F_i\}_{i=1}^N$, $\mathcal{D}$. ...

Wrapping up the last note of Feburary. The U of Chicago Symphony Orchestra performed Rachmaninoff Symphony No 2 today,The bundled piece is Too See the Sky, a contemporary violin concerto. Rachmaninoff’s Symphony No 2 touches on deep struggles of the composer’s inner thinking. I hear passages where the music suddenly swirls into dark passages, as if we enters through the composer’s unvisited despair. And, can modern composers stop bullying the piccolo? Giving piccolo exposed sixteenth scales in the lower register paired with impossible fingering — making the piccolo play everything that it’s not good at is not cool.

The academy nominated movie Tar (2022) tells a story of a fictional female conductor Lydia Tár. The film starts with Tár at the peak of her career (a protege of Leonard Bernstein, director of the Berlin Phil, finishing recording the last of her Mahler cycle). Some says the film is psychic, confusing, and somewhat creepy and haunting. Despite that Google autocompletes “What the heck is tar about” — the script is nice. Cate Blanchett did a great job. Music reference and orchestra scenes are highly accurate and professional. The movie’s deep. Reviews discuss a lot on Tár’s implied psychological nuance, feminism and anti-misogyny, as of the modern art world’s cancel culture, identity abuse (eg “I don’t like Bach because he’s straight and have 20 kids!”), and the long-argue about whether we should separate artist’s personal conduct with their work, etc etc. ...

Cross-country data reveals large total factor production (TFP) differences. This lecture asks: how does misallocation of inputs across heterogeneous firms affects measured sectoral TFP? Define and Measure Wedge in Monopolistic Competition Market Consider a market with final good producer, a continumm of intermediate good firms $i\in [0, 1]$, and households who supply labor inelastically at wage $W$ (taken as given by firms). The final good producer’s production function is $Y = \left( \int_0^1 Y_i^{\frac{\sigma-1}{\sigma}} \, \text{d}i \right)^{\frac{\sigma}{\sigma-1}}$. He maximizes $\max_{Y, \lbrace Y_i\rbrace}PY - \int P_i Y_i\,\text{di}$ take price as given. His maximization gives a demand function for each firm: ...