The impact of maize price shocks on household food security: Panel evidence from Tanzania

Using three waves (2008/09, 2010/11, 2012/13) of the Tanzanian National Panel Survey, this study investigates the impact of maize price shocks on household food security. Between 2008/09 and 2012/13, calorie intake stagnated for urban households, yet sharply deteriorated for rural households. The latter was driven by a significant decline in the consumption of the major staple maize which showed strongest price hikes among all major food items. Fixed-effects regressions indicate a clear negative relationship between maize prices and average household energy intake. Almost all population groups were found to be negatively affected by maize price shocks, with rural landless households being the most vulnerable group. In particular, a 50 percent rise in maize prices decreases caloric intake for rural (urban) households on average by 4.4 (5.4) percent, and for rural landless households by 12.6 percent. Results further indicate that subsistence agriculture can act as an effective strategy to insure against food price volatility.     

Sources of fluctuations in hours worked for Canada,Germany, Japan and the U.S.: a sign restriction VAR approach

This study empirically examines the sources of fluctuations in hours worked in Canada, Germany, Japan and the U.S. It is particularly motivated by Galí’s (1999) VAR study, which demonstrates that a positive technology shock reduces hours worked, at least in the short run. However, in the present study, a technology shock is identified without recourse to Galí’s long-run restriction, which has been subject to active controversy. Furthermore, this study uncovers other important sources of fluctuations in hours worked to reflect the concern, raised by numerous studies, that technology shocks leave most variations in hours worked unexplained. Specifically, there are six shocks underlying our model, and they are identified using a set of sign restrictions. The empirical results confirm that in all four countries, a positive technology shock significantly reduces hours worked. This technology shock, along with labor supply and demand shocks, accounts for most of the short-term variations in hours worked. As the forecasting horizon increases, technology and demand shocks become less important, whereas labor supply shocks contribute to explaining the bulk of long-run variations in hours worked. Finally, the empirical relevance of Galí’s long-run identification restriction is tested and the results are related to those obtained using the sign restriction model.     

Dynamic response of bank-intermediated trade finance to a global liquidity shock

This paper investigates the bank-level responses of a bank-intermediated instrument of trade finance to a negative global liquidity shock in Korea. Using a factor-augmented vector autoregression approach, the results show that there exists significant heterogeneity in bank-level trade-finance responses to a global liquidity shock. In addition, we find that the source of the heterogeneity is the bank-level foreign currency liquidity condition; banks with a better foreign currency liquidity condition may dampen the negative impact of a global liquidity shock on trade-finance.     

The impact of the COVID-19 pandemic on business expectations

We document and evaluate how businesses are reacting to the COVID-19 crisis through August 2020. First, on net, firms see the shock (thus far) largely as a demand rather than supply shock. A greater share of firms report significant or severe disruptions to sales activity than to supply chains. We compare these measures of disruption to their expected changes in selling prices and find that, even for firms that report supply chain disruptions, they expect to lower near-term selling prices on average. We also show that firms are engaging in wage cuts and expect to trim wages further before the end of 2020. These cuts stem from firms that have been disproportionally negatively impacted by the pandemic. Second, firms (like professional forecasters) have responded to the COVID-19 pandemic by lowering their one-year-ahead inflation expectations. These responses stand in stark contrast to that of household inflation expectations (as measured by the University of Michigan or the New York Fed). Indeed, firms’ one-year-ahead inflation expectations fell precipitously (to a series low) following the onset of the pandemic, while household measures of inflation expectations jumped markedly. Third, despite the dramatic decline in firms’ near-term inflation expectations, their longer-run inflation expectations have remained relatively stable.     

Liquidity shocks: A new solution to the forward premium puzzle

The frequent empirical failure of uncovered interest rate parity raises a question that has not been definitively answered: why do predictable excess returns on currencies persist in competitive currency markets? Supported by data from nine major currencies for 1978:08–2019:09, I provide a novel resolution to this enduring forward premium puzzle by building on the financial economics literature that explores the economic implications of limited access to capital markets. A liquidity shock, or the urgent demand for liquidity by credit-constrained arbitragers liquidating bond holdings, causes losses from sudden drops in bond prices. Arbitragers require a liquidity premium to compensate for potential losses that vary directly with the interest rate. It is this liquidity premium that explains persistent excess returns on currencies. I argue for policies favoring a low interest rate environment and macroprudential controls that ease liquidity constraints to increase the efficiency of international capital markets by reducing the liquidity premium.     

Do news shocks increase capital utilization?

Using the workweek of capital as a measure of capital utilization, we empirically test whether news shocks actually increase capital utilization. To this end, by estimating a panel VAR on two-digit manufacturing data identifying news shocks as innovations to stock returns orthogonal to the variations in current-period TFP growth, we find the positive response of capital utilization to news shocks. Moreover, to explain the positive response of capital utilization to news shocks in terms of plant-level investment behavior, we propose a heterogeneous plant model that combines the fixed cost of capital adjustment and an endogenous capital utilization choice. With the presence of fixed costs, except for the plants that have recently adjusted capital stock, news shock shortens the effective time horizon of currently installed capital stock and increases capital utilization. When the model economy is calibrated to match the salient features of the plant-level investment rate distribution, the economy generates a news-driven positive response of capital utilization.     

人工智能发展对通胀动态的影响及政策挑战——基于动态随机一般均衡模型的分析

人工智能的发展是生产力进步的表现，但广泛使用人工智能技术的经济效应尚待深入研究。基于人工智能对劳动的替代作用，将人工智能投资引入动态随机一般均衡模型，通过比较静态分析和短期动态分析考察人工智能发展对通胀动态的影响。稳态分析表明：人工智能投资效率提高和使用范围扩大均会提升劳动生产率进而提高产出水平，但对长期或趋势通胀没有影响；在人工智能发展初级阶段人工智能的发展会引起实际工资下降，而在相对高级阶段人工智能的发展会引起实际工资上升。短期动态分析显示：人工智能发展水平的提高，无论是投资效率的提高还是使用范围的扩大，都会导致通胀及实际边际成本对偏好冲击和技术冲击等外生冲击的反应变弱。人工智能的发展会使通胀动态与实际经济活动变化间的联系减弱，其原因是人工智能对劳动的替代作用使工资调整不再是应对外生冲击的必然选择，进而改变了外生冲击通过影响工资来影响通胀的传导机制。因此，发展人工智能在促进生产率提升和产出增长的同时，还会改变宏观经济变量间的传导机制，进而对通胀等政策调控目标变量的准确预测以及政策调整和实施的有效性带来新的挑战，也为金融理论研究提出新的课题。     

Exogenous shocks and managerial preparedness: A study of U.S. airlines’ environmental scanning before the onset of the COVID-19 pandemic

Managerial preparedness is a constant concern for firm stakeholders. This concern is exacerbated during times of immense stress brought about by exogenous shocks. In this paper, we analyze the preparedness of U.S. commercial airline management teams to the largest systematic exogenous shock to date, namely the COVID-19 pandemic in 2019 and 2020. We do this by underpinning the paper with theory on environmental scanning and managerial dysfunction and then documenting the signals and actions of management around multiple public health scares. These include the SARS outbreak, the Swine Flu outbreak and the COVID-19 outbreak. Our results, based off of corporate filings with the SEC, is that airline management had multiple “dry runs” before the COVID-19 outbreak that should have lead them to prepare for financially catastrophic scenarios such as the one observed in 2020. Instead, management teams failed to learn from these, and other, prior shocks. Instead, they focused on other, less serious threats while diffusing their financial buffers through dividends and share buybacks.     

基于车辆数据的k近邻联合概率数据关联算法

在交通场景中采用一些预警措施能够有效地减少交通事故发生。例如，对车辆轨迹进行跟踪并预测车辆的驾驶行为，就是一个常用的预警方法。在对车辆进行跟踪的过程中，数据关联是很重要的部分，它可以对车辆的观测点和轨迹进行关联，从而更新车辆的轨迹，完成跟踪过程。在此背景下，提出了一种新的数据关联算法，即k近邻联合概率数据关联算法(k Nearest Neighbor-Joint Probability Data Association,kNN-JPDA)。实验结果表明，该算法能够较好地解决在交通场景下车辆数据的数据关联问题，在精度以及运行效率方面都有所提高。