Large Shocks Research Articles

Should We Insure Workers or Jobs During Recessions?

What is the most efficient way to respond to recessions in the labor market? To this question, policymakers on the two sides of the pond gave diametrically opposed answers during the COVID-19 crisis. In the United States, the focus was on insuring workers by increasing the generosity of unemployment insurance. In Europe, instead, policies were concentrated on saving jobs, with the expansion of short-time work programs to subsidize labor hoarding. Who got it right? In this article, we show that far from being substitutes, unemployment insurance and short-time work exhibit strong complementarities. They provide insurance to different types of workers and against different types of shocks. Short-time work can be effective at reducing socially costly layoffs against large temporary shocks, but it is less effective against more persistent shocks that require reallocation across firms and sectors. We conclude that short-time work is an important addition to the labor market policy-toolkit during recessions, to be used alongside unemployment insurance.

A novel worm gear actuated repeatable locking/unlocking device for magnetically suspended control moment gyro

The locking/unlocking device (LUD) is crucial to protect the rotor in magnetically suspended control moment gyro (MSCMG) from vibration impacts during launch. Conventional LUDs have inevitable shortcomings in repeatability, compactness and reliability for aerospace applications. To overcome these disadvantages, this paper proposes a novel worm gear actuated repeatable locking/unlocking device (RLUD) consisting of an actuator, several transmission mechanism components and a locking nut. The configuration, working principle and design consideration are introduced in detail. Since the worm gear is a key component for torque transmission, the reliability analysis considering correlated failure modes of the tooth surface contact and tooth root bending is carried out by means of the fourth-order moment approach and copula function. The optimization design for the worm gear is subsequently implemented. The reliability analysis of the worm gear demonstrates that the assumption of independent failure modes without correlate consideration is likely to acquire conservative results, thus resulting in structural redundancy. Then, the optimization design is performed to achieve weight reduction under high reliability. The RLUDs based on optimization results are manufactured and then integrated into a prototype of MSCMG rotor system. Finally, a series of mechanics tests are conducted to evaluate the functional performance. The result of static load test shows that the strength and self-locking capacity of the RLUD are sufficient to support the compression load. The real-time response of the vibration signal indicates that the whole prototype is safe enough without any large shocks, thus satisfying the launch requirements. The relative displacements between the rotor and stator during vibrations are far less than the protective air gap, thus verifying the locking effect of the RLUD on the rotor.

Spread Too Thin: The Impact of Lean Inventories

Widespread adoption of just-in-time (JIT) production has reduced inventory holdings. This paper finds that JIT creates a trade-off between firm profitability and vulnerability to large shocks. Empirically, JIT adopters experience higher sales and less volatility while also exhibiting heightened cyclicality and sensitivity to natural disasters. I explain these facts in a structurally estimated general equilibrium model where firms can adopt JIT. Relative to a no-JIT economy, the estimated model implies a 1.3% increase in firm value. At the same time, an unanticipated shock results in a roughly 15% deeper output contraction. This occurs because firms "stock out" or hoard materials.

Normalization after Covid-19 Pandemic: Way Forward Towards Healthy Recovery

The world as we know has changed. While a global pandemic has been an ominous risk for decades, COVID-19 came as a jolt, characterized by the functional interdependencies of the social, economic and public health systems. The initial shock and systemic failures from policy unpreparedness, not only bared open the fault lines of social injustice and inequity, but also led to xenophobic orientation and conspiratorial thinking. Social isolation, mental health illness, redundancies, financial difficulties and permanent closure of many businesses were the fall out of this crisis. The world adapted and moved from physical to digital. Financial systems, education, industry and entertainment were restructured and decentralized. The pandemic also had significant effect on the sociopolitical trends including sense of human solidarity, rebuilding of national pride, work-home balance, reducing human impact on climate and the selfless dedication of health professionals.
 The pandemic’s chaos presented an opportunity to reevaluate priorities and develop new strategic solutions to the disruptions caused by tactical difficulties consequent to this plague. The interdependencies of our society, use of information technology and exceptional computational sciences, are the so-called new normal, the most appropriate way to do governance in an era of hyper connectedness. The pandemic has shown that economic and social determinants of ill-health are strong predictors of health outcome. There is a need to work for universal health coverage as it is in everyone’s interest that people who feel unwell should not check their pocket before they seek help. It is also imperative to integrate community-led services into public systems so as to enable universal access, Free healthcare is not only vital for tackling pandemics but it also prevents millions of people from falling into extreme poverty by the cost of healthcare every year. One also needs to strengthen social safety nets to enhance resilience, given the interrelation between health and livelihoods. Lastly, developing a common culture that emphasizes personal responsibility in the public interest, is essential. It is important to underscore that the biggest steps forward in health have usually happened in response to a major crisis as raising of post-Second World War health systems across Europe or establishment of NHS in United Kingdom.
 Thus, coronavirus crisis, first and foremost a health crisis, has complex and long-term consequences. Policy preparedness, financing our health, and business leadership are key to resilience against such large systemic shocks. It can therefore be seen as an important opportunity for largescale, deep-seated structural change, far beyond the obvious, in scale and scope.
 Editor-in-Chief
 
 How to cite this: Alamgir W, Gilani RA. Normalization after Covid-19 Pandemic: Way Forward Towards Healthy Recovery. Life and Science. 2022; 3(2): 64-64 . doi: http://doi.org/10.37185/LnS.1.1.250
 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

A novel rolling bearing fault diagnosis method based on generalized nonlinear spectral sparsity

In the fast kurtogram (FK), kurtosis is used as an indicator to locate the fault frequency band, and is widely aplied to fault diagnosis. However, kurtosis has been proven to favor a single large impulse rather than the required small fault characteristics, especially in the strong interference environment. To eliminate the impact of large-amplitude impact and further improve the accuracy of fault extraction, a method based on generalized nonlinear spectral sparsity (GNSS) is proposed for fault diagnosis of bearings. First, Z-score normalization and generalized nonlinear sigmoid activation function are used for signal preprocessing, and the scale distribution of the signal will be changed to eliminate the effects of large amplitude shocks under noisy environment. Then, to improve the sparsity measure capability, an improved L3/2 norm is used to replace kurtosis as the basis for selecting the best resonance frequency band. Finally, the effectiveness of the GNSS is verified by simulation data and experimental data. Compared with FK method, the performance of fault extraction of the proposed method is significantly improved, especially for the interference of abnormal impact.

Effect of Incident Angle of Wear-Ring Clearance on Pressure Pulsation and Vibration Performance of Centrifugal Pump

A wear-ring is an important part of the centrifugal pump. The leakage flow in the wear-ring clearance and main flow at the impeller inlet form crossed mixed flows perpendicular to each other. Large eddies and shocks are produced at the intersection of the two flows due to great velocity difference and different directions, resulting in flow losses, unsteady flow, and even flow-induced vibration. Consequently, the pump performance, pressure pulsation and vibration, and other characteristics will be greatly affected. In this paper, 5 incident angles between the incident section of the wear-ring clearance and the circumferential direction of impeller inlet, i.e., the original angle (90°), 75°, 60°, 45°, and 30°, were formed with a low-specific-speed centrifugal pump as the study object. Unsteady flow calculation and fluid–structure interaction calculation were performed on centrifugal pumps with different wear-ring clearances; the effect of the incident angle of the wear-ring clearance on the distribution of pressure pulsation and vibration performance of centrifugal pump was analyzed. The results showed that the improved efflux angle of the wear-ring clearance could effectively weaken the impact disturbance of the leakage flow in the wear-ring clearance to the main flow at the inlet. Accordingly, the flow status at the inlet of the centrifugal pump was improved, flow losses were reduced, the efficiency of the centrifugal pump was improved, and the vibration amplitude and vibration energy of the pump were also reduced.

Coping with shocks: How Self-Help Groups impact food security and seasonal migration

Combining seven years of household data from an original field experiment in villages of Jharkand, East India, with meteorological data, this paper investigates how Indian Self-Help Groups (SHGs) enable households to withstand rainfall shocks. I show that SHGs operate remarkably well under large covariate shocks. While credit access dries up in control villages one year after a bad monsoon, reflecting strong credit rationing from informal lenders, credit flows are counter-cyclical in treated villages. Treated households experience substantially higher food security during the lean season following a drought and increase their seasonal migration to mitigate expected income shocks. Credit access plays an important role, together with other SHG aspects such as peer networks. These findings indicate that local self-help and financial associations can help poor farmers to cope with climatic shocks and to implement risk management strategies.

Large Oil Shocks and Economic Growth: Evidence from Saudi Arabia

This paper aims to analyze the impact of large oil shocks on economic growth in Saudi Arabia, using a standard VAR model and a Markov-switching heteroscedastic regime, by using a quarterly data from 1981Q1 to 2019Q4. The results indicated that there were three large negative oil shocks, 1986Q1, 2008Q4, and 2014Q4, but there was only one large positive shock in 1990Q3. The impulse response and variance decomposition analysis show that both large negative and positive oil shocks have positive impacts on economic growth in Saudi Arabia, although only large negative shocks are statistically significant. Furthermore, large oil shocks only have a significant positive impact on economic growth comparing with normal oil shocks.

The fiscal response to revenue shocks

We study the impact of fiscal revenue shocks on local fiscal policy. We focus on the very volatile revenues from the immovable property gains tax in the canton of Zurich, Switzerland, and analyze fiscal behavior following large and rare positive and negative transitory revenue shocks. We apply causal machine learning strategies and implement the post-double-selection LASSO method to identify the effect of revenue shocks on public finances. We find that local policymakers predominantly smooth transitory fiscal shocks.

Outliers and Time-Varying Jumps in the Cryptocurrency Markets

We examine the presence of outliers and time-varying jumps in the returns of four major cryptocurrencies (Bitcoin, Ethereum, Ripple, Dogecoin, Litecoin), and a broad cryptocurrency index (CCI30). The results indicate that only Bitcoin returns are contaminated with outliers. Time-varying jumps are present in Bitcoin, Litecoin, Ripple, and the cryptocurrency index. Notably, the presence of jumps in Bitcoin is significant after correcting for outliers. The main findings point to a price instability in some major cryptocurrencies and thereby the importance of accounting for large shocks and time-varying jumps in modelling volatility in the debatable cryptocurrency markets.

Data Fitting with Rational Functions: Scaled Null Space Method with Applications of Fitting Large Scale Shocks on Economic Variables and S-Parameters

Curve fitting discrete data (x, y) with a smooth function is a complex problem when faced with sharply oscillating data or when the data are very large in size. We propose a straightforward method, one that is often overlooked, to fit discrete data (s, ys) with rational functions. This method serves as a solid data fitting choice that proves to be fast and highly accurate. Its novelty lies on scaling positive explanatory data to the interval [0, 1], before solving the associated linear problem Ax=0. A rescaling is performed once the fitting function is derived. Each solution in the null space of A provides a rational fitting function. Amongst them, the best is chosen based on a pointwise error check. This avoids solving an overdetermined nonhomogeneous linear system Ax=b with a badly conditioned and scaled matrix A. With large data, the latter can lack accuracy and be computationally expensive. Furthermore, any linear combination of at least one solution in the basis of the null space produces a new fitting function, which gives the flexibility to choose the best rational function that fits the constraints of specific problems. We tested our method with many economic variables that experienced sharp oscillations owing to the effects of COVID-19-related shocks to the economy. Such data are intrinsically difficult to fit with a smooth function. Deriving such continuous model functions over a desired period is important in the analysis and prediction algorithms of such economic variables. The method can be expanded to model behaviors of interest in other applied sciences, such as electrical engineering, where the method was successfully fitted into network scattering parameter measurements with high accuracy.

Valuation of Annuity Guarantees Under a Self-Exciting Switching Jump Model

This article investigates the valuation of annuity guarantees under a regime-switching model when the dynamics of the underlying stock price follow a self-exciting switching jump-diffusion process. In this framework, we add a jump component to a regime-switching geometric Brownian for large shocks on the stock price. The intensity of shock arrivals is a Hawkes process modulated by a continuous time hidden Markov chain with a finite number of states. The interest rate used for discounting is stochastic and correlated to the stock market. In an incomplete market, we define an equivalent martingale measure to price a variable annuity contract that guarantees a minimum living or death benefit. Under this equivalent martingale measure, we propose closed-form approximation formulas using the inverse Fourier transform technique. A numerical implementation highlights the impact of self-exciting jumps and economic regimes on the valuation of guarantees.

Fiscal adjustment in a panel of countries 1870–2016

The financial crisis from 2007 and, even more so, the Covid-19 pandemic caused large increases in public sector deficits and debts in many countries and prompted concern about fiscal adjustment. This paper examines fiscal adjustment to debt and deficits for a panel of 17 countries over 1870–2016 using the Jordà–Schularick–Taylor Macrohistory Database. This long span panel is informative since it contains many examples of large fiscal shocks similar to those recently experienced. The results from reduced-form models suggest that large deficits or surpluses tend to prompt stabilising feedbacks, mainly through changes in revenue, and there is greater pressure to adjust on countries running a deficit versus those running a surplus. However, the debt–GDP ratio prompts much less stabilising feedback by expenditure or revenue.11I am very grateful to Professor Ron P. Smith (Birkbeck, University of London) for all the useful comments and providing truly invaluable support in writing this paper. I also greatly appreciate very useful comments provided by an anonymous referee that helped to further enrich the paper.

Household consumption and exchange rate extreme dynamics: Multiple asymmetric threshold non‐linear autoregressive distributed lag model perspective

AbstractThis study re ‐evaluates the relative adjustments of household's consumption expenditure to extremely small and extremely large variations in exchange rate in African emerging economies (AEE). For this purpose, we used a modified version of non‐linear autoregressive distributed lag (ARDL) and multiple threshold non‐linear ARDL models that specifically captures the differential effects of extremely small and extremely large positive and negative variations of the explanatory variable(s) on the explained variable. Consequently, the empirical estimates reveal that changes in exchange rate has asymmetric effects on consumption expenditure in all the countries except in Nigeria. Furthermore, consumption expenditure in Algeria, Egypt and Morocco increases significantly at the upper quantile of exchange rate appreciation, whereas, it declines significantly at all quantiles of exchange rate depreciation, implying that consumption expenditure in these three North African countries are more sensitive to large positive shocks in exchange rate. In Kenya, Nigeria and South Africa, consumption expenditure are exchange rate inelastic as households maintain their consumption levels regardless of the direction and degree of exchange rate deviations. Overall, the diagnostics tests prove the superiority of this enhanced technique over the standard non‐linear ARDL technique. Based on the outcomes of this study, policy recommendations that could ensure optimal exchange rate alignment for the African countries, as well as other emerging economies have been proposed.

Collective investment in a common pool resource: Grower associations and food safety guidelines

AbstractCommon pool resources often face overexploitation, but collective action can counteract that tendency. We investigate collective investment in reputation for produce food safety, a common pool resource because of limited branding and traceability, by U.S. commodity organizations. We use a unique dataset constructed with data from U.S. Department of Agriculture, Food and Drug Administration, Centers for Disease Control and Prevention, and industry to provide novel evidence on collective investment in common pool resources. Notably, only large shocks to reputation such as foodborne disease outbreaks resulting in hospitalization increase the likelihood of food safety guideline adoption. Adoption of food safety guidelines by government‐backed organizations results in improvements in some food safety outcomes.

Aggregate demand externalities, income distribution, and wealth inequality

We study a two-class model of growth and the distribution of income and wealth at the intersection of contemporary work in classical political economy and post-Keynesian economics. The key insight is that aggregate demand is an externality for individual firms: this generates a strategic complementarity in production and results in equilibrium underutilization of the economy’s productive capacity, as well as hysteresis in real output. Underutilization also affects the functional distribution of income and the distribution of wealth: both the wage share and the workers’ wealth share would be higher at full capacity. Consequently, fiscal allocation policy that achieves full utilization also attains a higher labor share and a more equitable distribution of wealth; while demand shocks have permanent level effects. Extensions look at hysteresis in the employment rate and growth. These findings are useful as an organizing framework for thinking through the lackluster economic record of the so-called Neoliberal era, the sluggish recovery of most advanced economies following the Great Recession, and the importance of fiscal policy in countering large shocks such as the Covid-19 pandemic.

Multi-country SDGs indicator projections involving impacts of economic shocks: A protocol applied to the COVID-19 pandemic for ASEAN-5 countries

Economies often experience large shocks, necessitating the revision of development indicator forecasts, including Sustainable Development Goals (SDGs) indicators. Many of those, predicted for 2030, require continued monitoring and re-estimation of how great the impact of these shocks will be, e.g., comparing the achievements with and without the shocks (counterfactual). In this paper, we design a protocol to create datasets containing 2030 SDGs indicator projection estimates that can be used to monitor the extent to which current economic shocks will affect the trajectories of those indicators. We combine official United Nations Statistics Division (UNSTAT) SDGs indicator data and economic growth projections data and fit them into the protocol. The protocol includes filtering UNSTAT SDGs indicators for regression analysis connecting them with economic growth. We assume that the difference in economic growth projections before and after a shock is primarily caused by the shock. This implies that our protocol is less suitable for an episode of more subtle shocks or shocks with multiple causes. We use these estimates to create the SDGs indicators projection dataset. We applied this to ASEAN-5 countries and the COVID-19 pandemic. The same protocol can be used for other countries as well as other economic shocks.•The protocol is useful to monitor how previous projection trajectories of SDGs indicators are affected by relevant large economic shocks, such as those due to the COVID-19 pandemic. The resulted dataset can also be used for comparing achievements, with and without shocks (counterfactual).•This protocol can be used by national and international agencies, especially those in charge of planning, monitoring, and evaluating the SDGs agenda. The protocol and the resulting data would also be helpful to researchers working on SDGs issues.•In this paper, the protocol to create the projection dataset of SDGs applies for the ASEAN-5 countries using the COVID-19 shocks. These can also be applied for other countries and other economic shocks.

Inflation Dynamics and Food Prices in Hungarian Agricultural Economy

During 2021-2022, many commodity prices rose to record levels. As a result, Hungary in 2022 experiencing high inflation, large trade deficits, and an unstable macroeconomic environment. High commodity prices, particularly for food, also have adverse effects on poverty. Hungary has not experienced for a long time such increase in inflation, which is among the highest in Europe. Inflation growth has recently associated with large energy price shocks, food price increases are traditionally believed to have rather small effects. At the same time, there has been an absence of rigorous work to identify empirically the relative importance of each factor contributing to inflation. It is thus of vital importance to improve the understanding of the causes of inflation in Hungary to allow adequate policies to be put in place. The purpose of this paper is to fill this gap and thoroughly analyze the determinants of inflation in Hungary using data for the current decade, with a focus on food prices. The authors identify the relative importance of several factors contributing to overall inflation and its major components. The main finding is that, in a longer perspective, one of the main factors that determine domestic inflation are the food prices. In the short run, agricultural supply shocks strongly affect domestic inflation, causing large deviations from long-run price trends. The results suggest the need for a multi-pronged approach to fight inflation. This analysis suggest monetary and exchange rate policies need to take into account agricultural production, which is among the key determinants of inflation. Moreover it has a greater influence on inflation than is widely known.

Effects of Natural Resource exploitation on CEMAC Countries Development: The Human Capital Channel

Purpose: The aim of this study is to determine the effect of the exploitation of natural resources on the development of CEMAC countries and to examine human capital as a transmission channel. Design/methodology/approach: In order to achieve our goal, we formulate a panel of 6 CEMAC countries over the period 2002-2018. This period of study is justified by the surge in the prices of natural resources in the market and also a fall of the prices of basic resources following two large exogenous shocks (subprime crisis and 2015 oil crisis). The estimation method use is the fixe effect, two stage least square and the Maximum likelihood with limited information. Findings: Of the estimation by the fixed-effect method show that natural resources abundance measured by: total rent, oil rent and forest rent has a negative effect on economic development. Likewise, human capital contributes to the transmission of these effects. The minimum education rate beyond which natural resources no longer have a negative effect on economic development, measured by the logarithm of GDP, is approximately 0.52, 0.51 and 0.48 respectively when we consider the total rent, the oil rent and the forest rent. This result is confirmed with the adoption of Maximum likelihood with limited information and the Two Stage Least Squared. Research limitations/implications: This study is limited in time and space. Moreover, the failure to take into account certain human capital or development variables. Originality/value: In the literature on the natural resources curse, the analysis of transmission channels in developing countries remains largely unexplored. The human capital component studied in this article is one of the first in the case of CEMAC countries. Also, we studied the effect of many resources, both renewable and non-renewable.

(S)Cars and the Great Recession

United States households' consumption expenditures and car purchases collapsed during the Great Recession and more so than income changes would have predicted. Using CEX data, we show that both the extensive and the intensive car spending margins contracted sharply in the Great Recession. We also document significant cross‐cohort differences in the impact of the Great Recession including a stronger reduction in car spending by younger cohorts. We draw inference on the sources of the Great Recession by investigating which shocks can explain household choices in a 60 period life‐cycle model with idiosyncratic and aggregate shocks fitted to aggregate and life‐cycle moments. We find that the Great Recession was caused by a combination of large aggregate income and wealth shocks, while cross‐cohort adjustment patterns imply a role for life‐cycle income profile shocks. We also find a role for car loan premia shocks in accounting for car spending and car loans.