16:30〜18:00
Abstract: We develop an urban growth model where human capital spillovers foster entrepreneurship and learning in heterogeneous cities. Incumbent residents limit city expansion through planning regulations so that commuting and housing costs do not outweigh productivity gains from agglomeration. The model builds on strong microfoundations, matches key regularities at the city and economy-wide levels, and generates novel predictions for which we provide evidence. It can be quantified relying on few parameters, provides a basis to estimate the main ones, and remains transparent regarding its mechanisms. We examine various counterfactuals to assess the effect of cities on economic growth and aggregate output quantitatively.
16:45〜18:15
Abstract: This study proposes a tying maximum likelihood estimation (TMLE) method to improve the performance of estimation of statistical and econometric models in which most time series have long sample periods, whereas the other time series are very short. The main idea of the TMLE is to tie the parameters of the long time series with those of the short time series together so that some useful information in the long time series which is related to the short time series can be transferred to the short time series. The information transferred from the long series can help improve the estimation accuracy of the parameters related to the short series. We first provide asymptotic properties of the TMLE and show its finite-sample risk bound with a fixed tuning parameter which determines the strength of tying. Further, we provide a method for selecting the tuning parameter based on a bootstrap procedure. A finite sample theory about this method is derived, which tells us how to conduct the bootstrap procedure effectively. Extensive artificial simulations and empirical applications show that the TMLE has an outstanding performance in point estimate and forecast.
(登録者のみ参加可能)
17:00〜18:30
16:30〜18:00
要旨:New ideas and technologies adopted by a small number of individuals occasionally spread globally through a complex web of social ties. Here, we present a simple and general approximation method, namely, a message-passing approach, that allows us to describe the diffusion processes on (sparse) random networks in an almost exact manner. We consider two classes of binary-action games where the best pure strategies for individual players are characterized as variants of the threshold rule. We verify that the dynamics of diffusion observed on synthetic networks are accurately replicated by the message-passing equation, whose fixed point corresponds to a Nash equilibrium, while the conventional mean-field method tends to overestimate the size and frequency of diffusion. Generalized cascade conditions under which a global diffusion can occur are also provided. We extend the framework to analyze diffusion of multiple goods.
14:30〜15:30
Three Essays on Conglomerate Mergers
13:30〜14:30
Essays on Robust Social Preferences under Uncertainty
16:30〜18:00
要旨:携帯電話位置情報データを用いると、国全体などの広範囲の長距離旅行量とその詳細な時間的な変化をかなり精度よく把握できる。このデータを用いて2015年の北陸新幹線・金沢開業前後で前後1年間の比較をすると、所要時間が短縮された場所の変化だけでなく、新幹線で接続されていない西日本各地から石川県への来訪者の増加も大きくみられることがわかる。本研究では、後者のような空間パターンの変化に着目し、その特徴を解明するために、多時点の居住地-旅行先分布表を分解して、近年に発生した類似の変化を探索的に検出することを試みた。具体的には、都道府県あるいは市区町村単位の居住地・旅行先ペアごとの旅行先選択確率の変化を、対称行列(交通サービス変化による直接的な変化を含む対称な変化)と旅行先ごとに均一な値の入る行列(全国から均一に旅行者数を増やす効果)に分解した。その結果として、(1)居住地-旅行先表の経年変化は2種類の空間パターンでほとんど説明できること、(2) 北陸新幹線開業では後者のパターン変化が大きかったこと、(3)後者の効果は3年以上継続しており短期的な広告効果ではないこと、(4)後者の効果がない新幹線開業地も存在すること、などを明らかにした。
13:30〜14:30
Three Essays on Learning and Dynamic Coordination Games
16:45〜18:25
Yuuki Ozaki (Kyoto University)
板倉 大(京都大学)
16:45-17:15 Tomoya Hasegawa (Kyoto University) “Information and Behavior under Unawareness”
17:20-17:50 Yuuki Ozaki (Kyoto University) “Preferences with Multiple Reference Points”
17:55-18:25 板倉 大 (京都大学) “Communication with Reputation Concerns and Late State Revelation”