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We present a method for determining whether errors in expectations explain asset pricing puzzles without imposing assumptions about the error mechanism. Using accounting identities and survey forecasts, we find that errors in expected long-term inflation explain price variation, return predictability, and the rejection of the expectations hypothesis for aggregate stock and bond markets. Errors in short-term (long-term) nominal earnings growth expectations explain (do not explain) stock price variation and return predictability. The relevant errors are consistent with mistakes about the persistence of forecasted variables and the response to surprises. A simple framework based on fundamental extrapolation successfully replicates these findings. (JEL G40, G12, G14, E71) [ABSTRACT FROM AUTHOR]

In the overlapping global emergencies of the pandemic, climate change and geopolitical confrontations, supply shocks have become frequent and inflation has returned. This raises the question of how sector-specific shocks are related to overall price stability. This paper simulates price shocks in an input–output model to identify sectors which present systemic vulnerabilities for monetary stability in the United States. We call these prices systemically significant. We find that in our simulations the pre-pandemic average price volatilities and the price shocks in the COVID-19 and Ukraine war inflation yield an almost identical set of systemically significant prices. The sectors with systemically significant prices fall into four groups: energy, basic production inputs other than energy, basic necessities, and commercial infrastructure. Specifically, they are "Petroleum and coal products," "Oil and gas extraction," "Utilities," "Chemical products," "Farms," "Food and beverage and tobacco products," "Housing," and "Wholesale trade." We argue that in times of overlapping emergencies, economic stabilization needs to go beyond monetary policy and requires institutions and policies that can target these systemically significant sectors. [ABSTRACT FROM AUTHOR]

The post-pandemic surge in inflation was accompanied by a surge in the corporate share of profits. As a result, several economists and policy makers have given to it names such as "profit-led inflation" or "sellers' inflation." The present paper discusses the extent to which profit-led inflation, as an explanation for the recent surge in inflation, is compatible with what we know about the price-setting behavior of firms, income distribution, and inflation. We do that in juxtaposition to two recent critiques: that the increase in the profit share is the result of cyclical factors and that the increase in import prices leads to higher profit shares even under constant markups. We show that there is little evidence that the recent surge in profitability is cyclical in nature. Moreover, after outlining the Structuralist/Kaleckian theories of prices and inflation, we argue that profit-led inflation does not require an increase in the markup of the firms and is consistent with these theories. In the face of large import and other price shocks even under constant markups, firms are able to pass the burden of adjustment to real wages. Thus, the term profit-led emphasizes the distributional source and consequences of inflation. We also provide an empirical examination of the markups in the post-pandemic period using data from the Compustat database. We show that, on average, firms were able to increase or maintain their markups, although there is significant heterogeneity across sectors or the position of the firms in the distribution of markups. [ABSTRACT FROM AUTHOR]

We analyze how individual investors respond to inflation. We introduce a unique data set containing information on local inflation and security portfolios of more than 2,000 clients of a German bank between 1920 and 1924, covering the German hyperinflation. We find that individual investors buy fewer (sell more) stocks when facing higher local inflation. This effect is more pronounced for less sophisticated investors. Moreover, we document a positive relation between local inflation and forgone returns following stock sales. Our findings are consistent with individual investors suffering from money illusion. Alternative explanations, such as consumption needs, are unlikely to drive our results. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online [ABSTRACT FROM AUTHOR]

As inflation moderates at higher than optimal levels and real rates on 5-year Treasury inflation-protected securities (TIPS) are above 2 percent, TIPS become increasingly relevant. This column examines important issues associated with TIPS. Since TIPS are marked-to-market, their returns are much noisier than inflation bond returns. Clients can invest directly or indirectly in TIPS, and each has important advantages. Investors must be careful when comparing TIPS funds because reported yields sometimes include inflation and fund expenses (i.e., there is no uniformity among funds). Lastly, duration interpretation is a bit different for TIPS versus nominal bonds. [ABSTRACT FROM AUTHOR]

Construction projects are often procured through multidimensional auctions, in which suppliers bid on both price and non-price attributes such as quality. In Korea, a unique scaling method is employed to differentiate bids, adjusting scores to ensure a sufficient point difference between adjacent quality bids. This scaling method aims to enhance the discriminating power of the scoring system and attract more sophisticated project designs. However, it may distort overall bid rankings and lead to inefficient contract allocation. The added uncertainty may incentivize suppliers to inflate their prices, as the effect of price on winning probability decreases with the scaling factor. Using Korean procurement data, I analyse cases of rank reversal, and I reveal a tendency among suppliers to bid less aggressively on price when quality differences are magnified, with the effect varying with the level of uncertainty in bid evaluation. This highlights the preference of buyers for a less distortionary scoring system to enhance the value of procurement. [ABSTRACT FROM AUTHOR]

Over the past 25 years, trade flows have nearly quadrupled, and a renewed concern is whether trade openness is responsible for rising domestic inflation. This paper first provides a rigorous review and evidence of trade openness on domestic inflation by using a meta-analysis utilizing 31 years of empirical studies. The measurements of inflation, country and data characteristics, some macroeconomic variables (e.g. GDP, monetary supply, exchange rate) and econometric techniques are identified as the main contributions to the heterogeneity of previous findings. After checking for the presence of publication bias, the paper shows that the average effect of trade openness on domestic inflation is very small and barely significant, and the effect heterogeneity across the results is mainly explained by the studies' sample countries and their efforts to address the concern that trade openness might be endogenous. For studies in which endogeneity is well addressed, we find that trade openness could lead to inflation only in non-OECD countries but has no statistically significant effect in OECD countries. Therefore, the study suggests that the governments of these non-OECD countries should be aware of the side effects of trade openness. [ABSTRACT FROM AUTHOR]

Punctuated equilibrium theory (PET) describes policy change as occurring mostly through incremental movements with infrequent periods of dramatic change. An impressive body of empirical literature relating to budgeting supports this view, but virtually all empirical tests have focused on examining distributions of annual changes, thus nullifying chronology. In this article, we focus on the time element. Using the same databases as previously used in canonical PET studies, we explore multi-year trends, not only annual observations. For our analyses, we identify directional series of changes (while allowing for one-year changes in direction if these are immediately offset in the following year) on a U.S. budget distribution dataset covering the period of 1947 through 2014, with 60 categories of spending consistently defined over time and adjusted for inflation. We then assess the robustness of the PET findings when incorporating a longer time units of trending series of annual changes into the analysis. We find that almost 65% of changes occur in series of 4 years or more. Nonetheless, the signature PET literature pattern of high kurtosis is equally present in these series as well as in shorter series. Moreover, within growing and trending series, we find that 21% of these series generate 80% of positive budget change. Within these series, we identify a small group of "super-trends" that account for a large share of the overall change. We conclude that expanding methodologies for the study of budgetary change to incorporate longer-term dynamics helps to better understand policy change, but such findings remain consistent with the PET perspective. [ABSTRACT FROM AUTHOR]

In the last few years, the Federal Reserve, the European Central Bank and the Bank of Canada have all initiated policy reviews to reassess monetary policy tools and ideas that were no longer working in a changing global economy. In this paper, I argue that the debates that shaped these reviews can best be understood as 'knowledge controversies' in which some of the foundational metrics that monetary policies rely on themselves became the subject of debate. This unsettling of existing economic metrics poses not just technical but also political problems for central banks. These debates have eroded their efforts to depoliticise key issues, revealing the fragility of their technical fixes as metrics themselves can become the source of political disagreement both within the central banks themselves and in the wider public. As we enter an era of even more intense inflation-driven debates about central banking expertise and authority, these reviews provide insights into the epistemic dilemmas that central banks confront, suggesting that they will be dealing with knowledge controversies for some time to come. [ABSTRACT FROM AUTHOR]

This study analyzes the relationship between migration and inflation as well as the intervening role of interest rates in selected OECD countries from 1995 to 2020, covering periods of turbulence and tranquillity. The study finds that migration increases inflation in the short run but lowers it in the long run. In other words, the inflationary effect of migration is a long‐run phenomenon. Additionally, we find that the high interest rates help mitigate the inflationary effect of migration in the short run relative to the low interest rates. Moreover, additional analysis using the panel threshold technique further lends credence to the mediating role of interest rates in the nexus, thus making our results robust to alternative estimation techniques. These findings have significant implications for policymakers responsible for managing inflation. [ABSTRACT FROM AUTHOR]

This paper investigates the long-run and short-run relationship between trade openness and inflation for ECOWAS countries for the period 1970–2020. Using alternative openness measures and estimation methods, it was found that there is a significant positive long-run relationship between trade openness and inflation for ECOWAS countries. The implication of this result is that, if ECOWAS countries continue to import consumption products outside the region rather than capital goods that can increase domestic production, it will be very difficult for member countries to meet the convergence criteria, specifically low inflation required for the proposed monetary unification. In the short run, the results show that there is a negative relationship between trade openness and inflation for ECOWAS countries. This result is specific to a determined period and as the economy gets more open, it becomes more exposed to a higher rate of inflation. Therefore, to meet low inflation criteria, member countries should take it as a matter of urgency to fully implement the ECOWAS trade liberalization scheme to improve intra-regional trade. This would reduce excessive dependence on external imports which makes ECOWAS countries vulnerable to international price volatility, currency depreciation and a high rate of inflation. [ABSTRACT FROM AUTHOR]

In behavioral sciences, there is growing concern about the inflation of false-positive rates due to the amount of under-powered studies that have been shared in the past years. While problematic, having the possibility to recruit (lots of) participants (for a lot of time) is realistically not achievable for many research facilities. Factors that hinder the reaching of optimal sample sizes are, to name but a few, research costs, participants' availability and commitment, and logistics. We challenge these issues by introducing PsySuite, an Android app designed to foster a remote approach to multimodal behavioral testing. To validate PsySuite, we first evaluated its ability to generate stimuli appropriate to rigorous psychophysical testing, measuring both the app's accuracy (i.e., stimuli's onset, offset, and multimodal simultaneity) and precision (i.e., the stability of a given pattern across trials), using two different smartphone models. We then evaluated PsySuite's ability to replicate perceptual performances obtained using a classic psychophysical paradigm, comparing sample data collected with the app against those measured via a PC-based setup. Our results showed that PsySuite could accurately reproduce stimuli with a minimum duration of 7 ms, 17 ms, and 30 ms for the auditory, visual, and tactile modalities, respectively, and that perceptual performances obtained with PsySuite were consistent with the perceptual behavior observed using the classical setup. Combined with the high accessibility inherently supported by PsySuite, here we ought to share the app to further boost psychophysical research, aiming at setting it to a cheap, user-friendly, and portable level. [ABSTRACT FROM AUTHOR]

In any economy, inflation increases with an increase in economic growth and government size. However, when inflation increases beyond a certain undesirable level, it becomes a problem for the economy and hurts economic growth. The central bank uses various techniques to tackle inflation and reduce the possibility of harmful increase in it. Since India is a developing country, the government expenditure plays a crucial role and provides an important stimulus to economic growth. The main focus of this study is on the correlation between government spending and inflation in the country and its impact over the period 1983–2020. Along with that, the impact of gross domestic product and money supply has also been studied for the same time period. The results of the study suggest that in India, increase in an government expenditure causes an increase in inflation, and the other two variables also share a similar relationship with inflation. [ABSTRACT FROM AUTHOR]

This study examines the relationship between stock market development and economic growth in Nepal by employing autoregressive distributed lag (ARDL) model with bound testing procedures. The study period covers annual time series data from 1994 to 2019. Indicators of the stock market development used are size, depth and efficiency represented by market capitalization as a percentage of gross domestic product (GDP), total value of shares traded as a percentage of GDP and total shares traded as a percentage of market capitalization, respectively. Following high correlations among these indicators, an aggregated index is constructed and used in the study. Real GDP per capita growth is taken as an economic growth indicator. The results suggest that there exists a long-run uni-directional causality relationship running from stock market development index to economic growth. Stock market size and liquidity are significant contributors, showing that stock market is able to mobilize capital and diversify risks with increased easiness in trading of stocks. The control variable market inflation shows no significant impact on either of the examined primary variables. [ABSTRACT FROM AUTHOR]

The 2023 political year in the United States was dominated by three major themes: the legal problems of former President Donald Trump, particularly in light of his campaign to regain the White House in 2024; the near‐total dysfunctionality of the Republican majority in the House of Representatives; and the state of the economy, especially inflation, but also employment. Lurking in the background, and in large measure captive to these concerns, were the issues of immigration and aid to Israel and Ukraine. [ABSTRACT FROM AUTHOR]

Customizing text-to-image (T2I) models has seen tremendous progress recently, particularly in areas such as personalization, stylization, and conditional generation. However, expanding this progress to video generation is still in its infancy, primarily due to the lack of customized video data. In this work, we introduce Still-Moving, a novel generic framework for customizing a text-to-video (T2V) model, without requiring any customized video data. The framework applies to the prominent T2V design where the video model is built over a T2I model (e.g., via inflation). We assume access to a customized version of the T2I model, trained only on still image data (e.g., using DreamBooth). Naively plugging in the weights of the customized T2I model into the T2V model often leads to significant artifacts or insufficient adherence to the customization data. To overcome this issue, we train lightweight Spatial Adapters that adjust the features produced by the injected T2I layers. Importantly, our adapters are trained on "frozen videos" (i.e., repeated images), constructed from image samples generated by the customized T2I model. This training is facilitated by a novel Motion Adapter module, which allows us to train on such static videos while preserving the motion prior of the video model. At test time, we remove the Motion Adapter modules and leave in only the trained Spatial Adapters. This restores the motion prior of the T2V model while adhering to the spatial prior of the customized T2I model. We demonstrate the effectiveness of our approach on diverse tasks including personalized, stylized, and conditional generation. In all evaluated scenarios, our method seamlessly integrates the spatial prior of the customized T2I model with a motion prior supplied by the T2V model. [ABSTRACT FROM AUTHOR]

Since the COVID‐19 pandemic and the Russia–Ukraine War, global food markets have been in turmoil. Agricultural input and energy prices doubled between 2020 and 2022, with immediate consequences on food accessibility. We examine the drivers of the EU food inflation patterns, and how trade integration shapes these dynamics. We find that food price inflation has been mainly driven by surges in agricultural production costs and, to a lesser extent, by global food price increases. Trade openness has not exacerbated the inflating dynamics during this period. We conclude with reflections on inflationary, production, and trade policies. [ABSTRACT FROM AUTHOR]

We estimate government spending multipliers in demand‐ and supply‐driven recessions for the Euro Area. Multipliers in a moderately demand‐driven recession are two to three times larger than in a moderately supply‐driven recession, with the difference between multipliers being non‐zero with very high probability. More generally, multipliers are inversely correlated with the deviation of inflation from its trend, implying that the more demand‐driven a recession, the higher the multiplier. Multipliers range from −$$ - $$0.5 in supply‐driven recessions to about 2 in demand‐driven recessions. The econometric approach leverages a factor‐augmented interacted vector‐autoregression model purified of expectations (FAIPVAR‐X). The model captures the time‐varying state of the business‐cycle including strongly and moderately demand‐ and supply‐driven recessions, by taking the whole distribution of inflation deviations from trend into account. [ABSTRACT FROM AUTHOR]

We build a comprehensive database that categorizes COVID-19 fiscal measures announcements in 12 European Union countries into 7 distinct spending categories. Through our empirical analysis, we investigate the impact of these support packages on the economy. Overall, the fiscal measures played a crucial role in promoting output recovery without significant inflationary pressures. However, we observed substantial variations across different spending categories. Assistance provided to small and medium enterprises and specific sectors proved to be highly effective in stimulating the output while maintaining inflation. Direct pandemic spending and measures aimed at sustaining employment levels generated substantial output and employment multipliers and enhanced business sentiment without leading to inflationary costs. Conversely, universal help had inflationary effects and transfers to households primarily aroused consumer and business sentiment without producing significant economic impacts. [ABSTRACT FROM AUTHOR]

As worldwide food prices rise, there is a growing interest in understanding the effect of these increases on households. Building on previous work, while applying recent methodological advances, we focus our attention on México during the COVID-19 pandemic. We document these price escalations for a basket of foods representative of Mexican households' diets. The price increases are substantial across the basket, ranging from 20 percent in meat to 40 percent in tortilla. Using these estimates, we calculate the welfare effect from the recent food price escalation to cost households $17.07 billion annually, close to 1.5 percent of Mexico's Gross Domestic Product in 2020. We estimate households would need to increase their food expenditure budgets by 28.66 percent, the compensating variation, to achieve pre-price increase utility levels. [ABSTRACT FROM AUTHOR]

This paper shows that food price inflation varies across rural, urban, and metro counties in the United States. To quantify this disparity, we calculate food price indices using retail scanner data. Our indices suggest that between 2006 and 2020, rural areas had an overall higher food price inflation compared to urban and metro regions, with food price inflation averaging 0.7 percent lower in urban areas and 1.6 percent lower in metro areas. Additionally, we examine shifts in these disparities during key periods. We find that during the Great Recession, these differences were negligible, but in the post-Great Recession years, urban and metro areas consistently had lower food price inflation. However, the onset of the COVID-19 pandemic in 2020 led to a shift, with both urban and metro areas experiencing higher food price inflation, surpassing rural regions. [ABSTRACT FROM AUTHOR]

The issue of volatile food prices is a consistent problem for American consumers, as rising prices make it challenging to afford nutritious food that meets dietary standards. Various complex factors influence this price volatility, including economic conditions, weather patterns, global trade, energy prices, and more. Notably, the impact of food price increases is not equal for everyone. Low-income individuals and those in rural areas are disproportionately affected. A comprehensive understanding of the driving factors is essential to tackle this issue effectively. We employ advanced time-series techniques such as Vector Error Correction Models (VECM) and modern causal inference methods such as probabilistic graphical models implemented via machine learning and artificial intelligence approaches on monthly data from 2000 to 2021 to investigate the U.S. food price inflation issue. These methods help unravel the intricate dynamics among key variables driving food price inflation. The study aims to achieve several objectives. It intends to (1) clarify how factors influencing food price inflation in the U.S. change over time using VECM models, (2) establish causal relationships among interconnected variables to develop probabilistic graphical models using innovative search algorithms, and (3) create and validate forecasts related to U.S. food price inflation. The end goal is to provide actionable insights for policy design. Results show that food price inflation is heavily tied to commodity pricing and pricing for medical services. Additionally, historical decompositions for COVID-19 show ties between food price inflation and energy inflation. [ABSTRACT FROM AUTHOR]

This study aims to examine the relationship between interest rates and inflation in Pakistan, specifically considering the Fisher effect and the non-Fisher effect. The ongoing debate regarding whether raising interest rates contributes to higher inflation rather than effectively controlling it has motivated our research. To investigate this, we utilize time-varying vector auto-regressive and Granger causality tests. Our findings reveal the significance of the neo-Fisher effect, particularly from 2015 onwards, compared to the traditional Fisher effect in Pakistan. [ABSTRACT FROM AUTHOR]

AbstractWe make some initial attempt to establish the theoretical and methodological foundation for the model-X knockoffs inference for time series data. We suggest the method of time series knockoffs inference (TSKI) by exploiting the ideas of subsampling and e-values to address the difficulty caused by the serial dependence. We also generalize the robust knockoffs inference in [4] to the time series setting to relax the assumption of known covariate distribution required by model-X knockoffs, since such an assumption is overly stringent for time series data. We establish sufficient conditions under which TSKI achieves the asymptotic false discovery rate (FDR) control. Our technical analysis reveals the effects of serial dependence and unknown covariate distribution on the FDR control. We conduct a power analysis of TSKI using the Lasso coefficient difference knockoff statistic under the generalized linear time series models. The finite-sample performance of TSKI is illustrated with several simulation examples and an economic inflation study. [ABSTRACT FROM AUTHOR]

The two‐trials rule for drug approval requires "at least two adequate and well‐controlled studies, each convincing on its own, to establish effectiveness." This is usually implemented by requiring two significant pivotal trials and is the standard regulatory requirement to provide evidence for a new drug's efficacy. However, there is need to develop suitable alternatives to this rule for a number of reasons, including the possible availability of data from more than two trials. I consider the case of up to three studies and stress the importance to control the partial Type‐I error rate, where only some studies have a true null effect, while maintaining the overall Type‐I error rate of the two‐trials rule, where all studies have a null effect. Some less‐known P$$ P $$‐value combination methods are useful to achieve this: Pearson's method, Edgington's method and the recently proposed harmonic mean χ2$$ {\chi}^2 $$‐test. I study their properties and discuss how they can be extended to a sequential assessment of success while still ensuring overall Type‐I error control. I compare the different methods in terms of partial Type‐I error rate, project power and the expected number of studies required. Edgington's method is eventually recommended as it is easy to implement and communicate, has only moderate partial Type‐I error rate inflation but substantially increased project power. [ABSTRACT FROM AUTHOR]

We extend the analytic description of complex no-boundary solutions in the context of inflation to large field models. We discuss the Kontsevich–Segal–Witten (KSW) criterion and find it is satisfied in small field models, while in large field models it depends on an integral involving V ′ (ϕ) over the range of inflation. It follows that although particular models are ruled out, e.g. quadratic inflation, the criterion does not truly constrain inflationary phenomenology since any inflation potential can be completed beyond observable scales so as to satisfy KSW. [ABSTRACT FROM AUTHOR]

Innovation is a complex subject. Scholars have identified its systemic and evolutionary nature. Different institutions, such as firms, universities, and government, must undertake this endeavor conjointly. In Brazil, certain macroeconomic conditions are averse to innovation. This compels firms to adapt to the imperatives of competition and make a constant effort to innovate and aggregate value to their products. Here the Brazilian Defense Industrial Base is analyzed within the framework of the general economic macroenvironment. The main indicators that foster innovation are absent in Brazil, making the challenge even more complex and risk prone. The same occurs with the defense sector, where besides some exceptions, firms must count on special incentives and international collaboration if they are to attempt innovating. The argument put forward here refers to the vicious macroeconomic cycle in which high interest rates, devaluated currency and inflationary pressure dampen innovative efforts. This is mirrored in the defense sector where there is the aggravator of the composition of defense expenditures which works in the opposite way of investment and reequipment. [ABSTRACT FROM AUTHOR]

Many individually randomized group treatment (IRGT) trials randomly assign individuals to study arms but deliver treatments via shared agents, such as therapists, surgeons, or trainers. Post‐randomization interactions induce correlations in outcome measures between participants sharing the same agent. Agents can be nested in or crossed with trial arm, and participants may interact with a single agent or with multiple agents. These complications have led to ambiguity in choice of models but there have been no systematic efforts to identify appropriate analytic models for these study designs. To address this gap, we undertook a simulation study to examine the performance of candidate analytic models in the presence of complex clustering arising from multiple membership, single membership, and single agent settings, in both nested and crossed designs and for a continuous outcome. With nested designs, substantial type I error rate inflation was observed when analytic models did not account for multiple membership and when analytic model weights characterizing the association with multiple agents did not match the data generating mechanism. Conversely, analytic models for crossed designs generally maintained nominal type I error rates unless there was notable imbalance in the number of participants that interact with each agent. [ABSTRACT FROM AUTHOR]

We quantify two hypotheses: the "Friedman-Ball Hypothesis" and the "Cukierman-Meltzer Hypothesis," in the context of Bangladesh. The first posits that an increase in inflation leads to greater inflation uncertainty, while the second asserts that inflation uncertainty causes an increase in inflation. Using monthly inflation data from June 1997 to July 2021, we find evidence supporting both hypotheses. Our analysis of inflation persistence and structural breaks reveals that inflation in Bangladesh exhibits high persistence throughout the entire sample period, but there is a decrease in persistence in two of the sub-samples after the breaks in March 2007 and April 2012. Moreover, Bangladesh's inflation persistence is comparable to, and at times even lower than, that of its South and Southeast Asian neighboring countries. As policy implications of our findings, we emphasize the need for a more nuanced approach to monetary policy, including proactive interest rate management, implementation of a Medium-Term Fiscal Framework, and the development of a flexible monetary policy strategy tailored to Bangladesh's unique economic circumstances. [ABSTRACT FROM AUTHOR]

There is a growing interest in clinical trials that investigate how patients may respond differently to an experimental treatment depending on the basis of some biomarker measured on a continuous scale, and in particular to identify some threshold value for the biomarker above which a positive treatment effect can be considered to have been demonstrated. This can be statistically challenging when the same data are used both to select the threshold and to test the treatment effect in the subpopulation that it defines. This paper describes a hierarchical testing framework to give familywise type I error rate control in this setting and proposes two specific tests that can be used within this framework. One, a simple test based on the estimated value from a linear regression model with treatment by biomarker interaction, is powerful but can lead to type I error rate inflation if the assumptions of the linear model are not met. The other is more robust to these assumptions, but can be slightly less powerful when the assumptions hold. [ABSTRACT FROM AUTHOR]

Foreign exchange rate is one of the main macroeconomic variables that affect the economy of a country. Exchange rate affects the level of investment in a country, price stability and the balance of trade. Various macroeconomic factors have been identified by various authors as contributing to fluctuation in exchange rate. This includes among others relative inflation, interest rates, income levels, government interventions and market expectations. The aim of this study was to investigate the relationship between inflation volatility and exchange rate fluctuation in Kenya. The study relied on the hypothesis of purchasing power parity theory of existence of a negative relationship between inflation and exchange rate movement. The research aimed at establishing the extent to which the Purchasing Power Parity (PPP) theory holds in Kenya. The research was for a period of nine years from January 2005 up to December 2013.Secondary data for exchange rate movement were obtained from the Central Bank of Kenya while data for inflation was obtained from the Kenya National Bureau of Statistics. This two are government institutions and therefore the credibility of data was assured. Regression analysis was applied to analyze the data in order to establish the relationship that exists between the two variables. The result from data analysis indicates the existence of a moderate negative relationship between movement in inflation and exchange rate volatility. This finding therefore supports the existence of PPP concept in Kenya during the period of study. The finding also indicates other factors also greatly influence movement in exchange rate and therefore inflation cannot be relied up on as the sole factor determining exchange rate. [ABSTRACT FROM AUTHOR]

This paper investigates the long-debated economic relationship between prices and interest rates through two macroeconomic relationships, the Gibson paradox and the Fisher effect. We use recent advances in applied econometrics and quarterly frequency data for the G7 (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States) and E7 (Brazil, China, India, Indonesia, Mexico, Russia, and Turkey) countries. We also use the Schmelzing (2019) new data on advanced economy inflation rates and interest rates to investigate the Fisherian link in eight advanced economies (France, Germany, Holland, Italy, Japan, Spain, the United Kingdom, and the United States) across eight centuries. The overall conclusion of the paper demonstrates poor evidence of the Gibson paradox and the Fisher effect across developed and emerging economies. [ABSTRACT FROM AUTHOR]

Leading central banks did not anticipate the surge in inflation in 2021 and 2022. In our paper we assess whether changes in the velocity of money and monetary growth (broadly defined) explain long term inflation patterns in the US. We use a hundred-year sample to study the long term and the cyclical behaviour of money velocity. We find that changes in the velocity of money are short lived and revert to its mean. We also characterise the periods where changes in money velocity have kept closer to its mean as those of monetary equilibrium. We use a regime switching model to test for the impact of changes in the amount of money (broadly defined) and in money velocity in inflation over the medium and long term. Our model explains both the non-inflationary outcome of the Global Financial Crisis and the surge in inflation in the aftermath of the Covid-19 pandemic. [ABSTRACT FROM AUTHOR]

Considering the consumption‐induced intensification of global challenges and the continuously changing consumer needs, it is important to understand the drivers of consumer food choices under external pressures. We applied best–worst scaling to elicit the relative importance of 11 food values and conducted latent class cluster analyses based on individual scores, allowing us to gain insights into distinctive consumer segments. Data were collected through online surveys of 1000 consumers in Bavaria, southern Germany, in November 2020 and November 2022. As expected, the relative importance of food value price has strongly increased during this period. Similarly, the price‐sensitive segment has become larger in 2022 than in 2020, while the societal impact‐centered segment has become much smaller in 2022. These findings call for target‐specific measures to counteract this trend of increasing price focus that challenges sustainable dietary transitions. [ABSTRACT FROM AUTHOR]

This paper examines the impact of retail e-commerce on pricing behavior and welfare. Using Japanese data, we find that e-commerce lowered relative inflation rates for goods sold intensively online. We use long time series and historical catalog sales as an instrument for e-commerce sales intensity. The entry of e-commerce firms raised the rate of intercity price convergence in physical stores for goods sold intensively online, but not for other goods, which suggests e-commerce enhances price arbitrage. We estimate that e-commerce lowered variety-adjusted prices on average by 0. 9 % between 1996 and 2014, and more in cities with highly educated populations. [ABSTRACT FROM AUTHOR]

We develop a framework for measuring under- and overreaction in expectation formation. The basic insight is that under- and overreaction to new information is identified (up to sign) by the impulse response function of forecast errors. Our measurement procedure yields estimates of under- and overreaction to different shocks at various horizons. In an application to inflation expectations, we find that forecasters underreact to aggregate shocks but overreact to idiosyncratic shocks. We illustrate how our approach can be used to (i) quantify the importance of different biases, (ii) estimate theoretical models, and (iii) shed light on existing empirical approaches and puzzles. [ABSTRACT FROM AUTHOR]

We study how misperceptions of others' tastes influence beliefs, demand, and prices in markets with observational learning. Consumers infer a good's quality from the quantity demanded and price paid by others. When consumers exaggerate the similarity between their and others' tastes, such "taste projection" generates discrepant quality perceptions, which are decreasing in a projector's taste and increasing in the observed price. These biased inferences produce an excessively elastic market demand. We also analyze dynamic monopoly pricing with short-lived taste-projecting consumers. Optimal pricing follows a declining path: a high initial price inflates future buyers' perceptions, and lower subsequent prices induce overadoption. (JEL D42, D83, D91, L15) [ABSTRACT FROM AUTHOR]

Add ons are features or services that can enhance the functionality or quality of base goods. They are pervasive. Yet we know little about the behavior of add‐on prices over the business cycle. We use 10 years of data from a nationwide Canadian retailer to investigate the local cyclicality of extended warranty prices, a classic add on. We find base prices are acyclical. Warranty prices are procyclical because local stores use warranties to make demand for durable goods less price‐elastic. We show add ons amplify responses to national business cycles and study the implications for inflation rate bias. [ABSTRACT FROM AUTHOR]

This study utilised longitudinal data from Black History Month events in London from 2021 to 2023. Novel findings revealed that increased inflation and Bank Rates, related to the cost-of-living crisis, were associated with greater discrimination and deteriorations in both general and mental health for Black individuals. Moreover, it was found that during the cost-of-living crisis period, i.e. 2022–2023, discrimination was more adversely related to general and mental health deterioration compared to the period before the cost-of-living crisis, i.e. 2021. In addition, women, non-native individuals, non-heterosexual individuals, the unemployed, economically inactive individuals, those with lower educational attainment, and older individuals experienced higher levels of discrimination and reduced general and mental health compared to reference groups. The findings of the study contribute to the literature by demonstrating the intertwined associations of macroeconomic deteriorations and discrimination with the health of the Black community, and its subgroup differences, providing a basis for targeted policies. [ABSTRACT FROM AUTHOR]

The effect of inflation on income inequality is uncertain in both theoretical and empirical literature. This article investigates whether institutions matter in this relationship, using the corruption perception index and economic freedom index as representatives. The article focuses on the two-step system generalized method of the moments results from 2012 to 2018 for 58 countries; however, for the sake of comparing results, pooled ordinary least squares, fixed effect estimations and difference generalized method of moments are employed. The findings suggest that inflation has a robust negative effect on income inequality. Good institutions, low corruption and high economic freedom levels lead to income inequality, and their overall effect shows that (i) a decrease in corruption and an increase in economic freedom cause the effect of high inflation turn positive on income inequality, (ii) high inflation rates eliminate good institutions' reducing effect on income inequality. The study contributes to the limited literature on the relationship between inflation and income inequality. It distinguishes itself from the literature by examining the role of institutions in this relationship by using corruption and income inequality together. [ABSTRACT FROM AUTHOR]

This paper examines networks of n measuring parties sharing m nonsignaling resources that can be locally wired together: that is, each party follows a scheme to measure the resources in a cascaded fashion with inputs to later resources possibly depending on outputs of earlier-measured ones. A specific framework is provided for studying probability distributions arising in such networks, and this framework is used to directly prove some accepted, but often only implicitly invoked, facts: there is a uniquely determined and well-defined joint probability distribution for the outputs of all resources shared by the parties, and this joint distribution is nonsignaling. It is furthermore shown that is often sufficient to restrict consideration to only extremal nonsignaling resources when considering features and properties of such networks. Finally, the framework illustrates how the physical theory of nonsignaling boxes and local wirings is causal, supporting the applicability of the inflation technique to constrain such models. For an application, we probe the example of (3 , 2 , 2) inequalities that witness genuine three-party nonlocality according to the local-operations-shared-randomness definition, and show how all other examples can be derived from that of Mao et al (2022 Phys. Rev. Lett. 129 150401). [ABSTRACT FROM AUTHOR]