Essays on Business Cycles and Stabilization Policy.

This dissertation is a collection of essays on fiscal policy, monetary policy and the international transmission of business cycle shocks. Chapter 1 highlights the importance of distinguishing durable and nondurable goods when conducting countercyclical fiscal policy. It shows that the fiscal multiplier for purchases of durable goods is much smaller than the multiplier for nondurable goods. Standard models predict small durables multipliers because private sector purchases of durable goods are highly intertemporally substitutable and therefore easily crowded out. Empirical estimates based on U.S. data confirm this result. In aggregate time series data output rises by about 50 cents less if the government purchases 1$ of durable rather than nondurable goods. Industry-level estimates also point to smaller durable goods multipliers. The findings of this chapter suggest that infrastructure spending which is frequently part of fiscal stimulus packages is relatively ineffective at raising aggregate demand. Chapter 2, joint with Christopher L. House, shifts focus to monetary policy and analyzes the optimal Taylor rule in a standard New Keynesian model. If the central bank can observe the output gap and inflation without error, then it is typically optimal to respond infinitely strongly to observed deviations from the central bank’s targets. If it observes inflation and the output gap with error, the central bank will temper its responses so as not to impart unnecessary volatility to the economy. If the Taylor rule is expressed in terms of estimated output and inflation then it is optimal to respond infinitely strongly to estimated deviations from the targets. Under such a Taylor rule the estimates of inflation and the output gap should be perfectly negatively correlated. In the data, inflation and the output gap are weakly correlated, suggesting that the central bank is systematically underreacting. Chapter 3, joint with Aaron Flaaen and Nitya Pandalai-Nayar, studies the cross-country transmission of shocks. Using the 2011 Tohoku earthquake as a natural experiment, the study shows that firms reliant on Japanese intermediates experienced significant drops in production after the disruption. These findings imply that supply chains are sufficiently inflexible to play an important role in the international transmission of shocks.PhDEconomicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120791/1/chrisboe_1.pd

Government Spending and Durable Goods

This paper shows that the fiscal multiplier for purchases of durable and investment goods is very small - much smaller than the multiplier for nondurable goods. Standard models predict small durables multipliers because private sector purchases of durable goods are highly intertemporally substitutable and therefore easily crowded out. Empirical estimates based on U.S. data confirm this result. In aggregate time series data output rises by about 50 cents less if the government purchases 1$ of durable rather than nondurable goods. At the industry level, spending on durable goods leads to smaller sectoral expansions than spending on nondurable goods. The findings of this paper suggest that infrastructure spending which is frequently part of fiscal stimulus packages is relatively ineffective at raising aggregate demand

SmartTrack: Efficient Predictive Race Detection

Widely used data race detectors, including the state-of-the-art FastTrack algorithm, incur performance costs that are acceptable for regular in-house testing, but miss races detectable from the analyzed execution. Predictive analyses detect more data races in an analyzed execution than FastTrack detects, but at significantly higher performance cost. This paper presents SmartTrack, an algorithm that optimizes predictive race detection analyses, including two analyses from prior work and a new analysis introduced in this paper. SmartTrack's algorithm incorporates two main optimizations: (1) epoch and ownership optimizations from prior work, applied to predictive analysis for the first time; and (2) novel conflicting critical section optimizations introduced by this paper. Our evaluation shows that SmartTrack achieves performance competitive with FastTrack-a qualitative improvement in the state of the art for data race detection.Comment: Extended arXiv version of PLDI 2020 paper (adds Appendices A-E) #228 SmartTrack: Efficient Predictive Race Detectio

The Effects of Selective Inhibition of Histone Deacetylase 1 and 3 in Huntington’s Disease Mice

Huntington's disease (HD) is an autosomal dominant neurodegenerative disease characterized by a late clinical onset of psychiatric, cognitive, and motor symptoms. Transcriptional dysregulation is an early and central disease mechanism which is accompanied by epigenetic alterations in HD. Previous studies demonstrated that targeting transcriptional changes by inhibition of histone deacetylases (HDACs), especially the class I HDACs, provides therapeutic effects. Yet, their exact mechanisms of action and the features of HD pathology, on which these inhibitors act remain to be elucidated. Here, using transcriptional profiling, we found that selective inhibition of HDAC1 and HDAC3 by RGFP109 alleviated transcriptional dysregulation of a number of genes, including the transcription factor genes Neurod2 and Nr4a2, and gene sets and programs, especially those that are associated to insulin-like growth factor pathway, in the striatum of R6/1 mice. RGFP109 treatment led to a modest improvement of the motor skill learning and coordination deficit on the RotaRod test, while it did not alter the locomotor and anxiety-like phenotypes in R6/1 animals. We also found, by volumetric MRI, a widespread brain atrophy in the R6/1 mice at the symptomatic disease stage, on which RGFP109 showed no significant effects. Collectively, our combined work suggests that specific HDAC1 and HDAC3 inhibition may offer benefits for alleviating the motor phenotypic deficits and transcriptional dysregulation in HD

Plasma-Functionalized Water: from Bench to Prototype for Fresh-Cut Lettuce

Fresh-cut produce like lettuce may contain a very high microbial load, including human pathogens. Therefore, the need for antimicrobial agents at post-harvest stages to mitigate microbial cross-contamination and growth is evident. Sanitation based on non-thermal plasma (NTP) reveals innovative food processing possibilities by application at different points along the food chain, for production, modification, and preservation, as well as in packaging of plant- and animal-based food. The aim of the present study was to evaluate the applicability of plasma-treated water (PTW) as antimicrobial process water additives for washing in fresh-cut lettuce processing. Antibacterial activities of PTW the natural occurring microflora of lettuce were examined. Different process variants of PTW application inside the washing process were investigated. Fresh-cut lettuce were investigated regarding microbiological safety and food quality. Samples were analyzed for antimicrobial and metabolic activity as well as metabolic vitality to prove food safety. The investigations for food quality included color and texture analyses and nitrate concentration detection in fresh tissue as well as microscopic measurements by scanning electron microscopy (SEM) and atomic force microscopy (AFM) for tissue surface structure and transmission electron microscopy (TEM) for cell organelle investigations. The application of PTW allowed up to 5 log10 cycle reduction, depending on the process variant and scale (lab and pilot scale). The increase of antimicrobial activity was accompanied by a reduction of metabolic activity, but not consequently by a decrease in metabolic vitality. Food quality was not affected by the use of PTW in the washing process of the fresh-cut lettuce. The promising results in color and texture were supported by the results of the microscopic assays. These promising results may lead to an industrial application of PTW as process water additive in fresh-cut produce processing to reduce the microbial load on the food surface and in addition in the process water or on food processing surfaces. © 2020, The Author(s)

A Semiquantitative Non-invasive Measurement of PcomA Patency in C57BL/6 Mice Explains Variance in Ischemic Brain Damage in Filament MCAo

Numerous studies on experimental ischemic stroke use the filament middle cerebral artery occlusion (fMCAo) model in C57BL/6 mice, but lesion sizes in this strain are highly variable. A known contributor is variation in the posterior communicating artery (PcomA) patency. We therefore aimed to provide a semiquantitative non-invasivein vivomethod to routinely assess PcomA patency. We included 43 male C57BL/6 mice from four independent studies using a transient 45 min fMCAo model. Edema-corrected lesion sizes were measured by magnetic resonance (MR) imaging 24 h after reperfusion. Time-of-flight MR angiography was performed 7 days before and 24 h after fMCAo. Scores of PcomA size measured 24 h after, but not scores measured 7 days before fMCAo were negatively correlated with lesion size. Variability in PcomA patency explained 30% of the variance in our cohort (p< 0.0001, coefficient of determinationr(2)= 0.3). In a simulation using parameters typical for experimental stroke research, the power to detect a true effect ofd= 1 between two groups increased by 15% when an according covariate was included in the statistical model. We have demonstrated thatin vivomeasurement of PcomA size is feasible and can lead to increased accuracy in assessing the effect of treatments

Working memory load for faces modulates P300, N170, and N250r

We used event-related potential (ERP) methodology to examine neural activity associated with visual working memory (WM) for faces. There were two main goals. First, to extend previous findings of P300 load modulation to WM for faces. Second, to examine whether N170 and N250r are also influenced by WM load. Between one and four unfamiliar faces were simultaneously presented for memory encoding. After a 1-sec delay, a target whether this face was part of the previous face array. P300 amplitude decreased as WM load increased, and this P300 suppression was observed at both encoding and retrieval. WM load was also found to modulate other ERPs. The amplitude of the N170 elicited by the target face decreased with load, and this N170 decrease leveled off at load 2, reflecting the behavioral WM capacity of around two faces. In addition, the N250r, observed as an ERP difference for target faces that were present in the encoding array relative to target faces that were absent, was also reduced for higher WM loads. These findings extend previous work by showing that P300 modulation by WM load also occurs for faces. Furthermore, we show, for the first time, that WM load affects the N250r and the early visual N170 component. This suggests that higher visual areas play an important role in WM for faces

Refined movement analysis in the staircase test reveals differential motor deficits in mouse models of stroke

Accurate assessment of post-stroke deficits is crucial in translational research. Recent advances in machine learning offer precise quantification of rodent motor behavior post-stroke, yet detecting lesion-specific upper extremity deficits remains unclear. Employing proximal middle cerebral artery occlusion (MCAO) and cortical photothrombosis (PT) in mice, we assessed post-stroke impairments via the Staircase test. Lesion locations were identified using 7 T-MRI. Machine learning was applied to reconstruct forepaw kinematic trajectories and feature analysis was achieved with MouseReach, a new data-processing toolbox. Lesion reconstructions pinpointed ischemic centers in the striatum (MCAO) and sensorimotor cortex (PT). Pellet retrieval alterations were observed, but were unrelated to overall stroke volume. Instead, forepaw slips and relative reaching success correlated with increasing cortical lesion size in both models. Striatal lesion size after MCAO was associated with prolonged reach durations that occurred with delayed symptom onset. Further analysis on the impact of selective serotonin reuptake inhibitors in the PT model revealed no clear treatment effects but replicated strong effect sizes of slips for post-stroke deficit detection. In summary, refined movement analysis unveiled specific deficits in two widely-used mouse stroke models, emphasizing the value of deep behavioral profiling in preclinical stroke research to enhance model validity for clinical translation.Peer Reviewe