The Review of Keynesian Studies
Online ISSN : 2435-6581
最新号
選択された号の論文の8件中1~8を表示しています
Articles
  • Marco Guerrazzi
    2023 年 5 巻 p. 1-21
    発行日: 2023年
    公開日: 2023/10/27
    ジャーナル フリー

    In this paper, relying on the seminal Keynesian analysis of the market for goods, I aim at integrating the market-period adjustments of relative-price expectations with the short-run dynamics generated by the occurrence of demand shocks and the long-run dynamics implied by capital accumulation and supply shocks. Specifically, I build a dynamic setting in which output, (un)employment and real wages tend to converge towards a non-deterministic short-run equilibrium pinned down by long-run entrepreneurial expectations. Furthermore, calibrating the model economy by taking as reference the US economy, I show that the cyclical properties of the resulting theoretical framework are consistent with a number of observed business cycle regularities.

  • Ken Matsumoto
    2023 年 5 巻 p. 22-46
    発行日: 2023年
    公開日: 2023/10/27
    ジャーナル フリー

      By solving a dynamic optimization structure, this paper aims to achieve an optimal monetary policy which enables the central bank to minimize a Taylor-rule embedded social loss function of inflation and employment. Three different types of inflation expectations are tested: forward-looking, backward-looking, and mixed expectation formation. As a result, under several assumptions, we found stable and optimal policy paths with all of the three scenarios. The results suggest that when the expected inflation rate is below the target, the central bankers need to initially set the interest rate at a sufficiently low level but gradually raise it, until they reach the equilibrium. Opposite solution stands if the inflation expectation is above the target. These may be counterfactual to a commonly seen monetary policy, though we believe this analysis is meaningful, in a way that our solution can be regarded as a “reference” or “yardstick”, and indicate how the real-life monetary policy is deviating from the optimal path.

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