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The Federal Open Market Committee (FOMC) releases quarterly its members’ views about what federal funds rate will be appropriate at the end of the current and the next two or three years, and in the “longer run.” We construct constant horizon interest rate projections one, two and three years ahead and use real-time data on 32 important macroeconomic time series to study how these variables impact on the FOMC’s interest-rate setting. News regarding the labour market is particularly important at all horizons. At longer horizons, financial market, trade and output news also matter.

We adapt the design of four experimental studies on retirement decision-making and conduct replications with a larger online sample from the broader population. We replicate most of the main effects of the original studies. In particular, we confirm that consumption decisions are less efficient when subjects need to borrow from the future than when they need to save from the present. When subjects collect retirement benefits as lump sum instead of annuities, they choose to retire later, as suggested by the original study. We also confirm that savings are higher when they are incentivized with matching contributions than when incentivized with tax rebates. However, when faced with varying survival risks, subjects in our replication make only partial adjustments to spending paths when ambiguity is reduced. We also propose a further experimental research agenda in related topics and discuss practical issues on subject recruitment, attrition, and redesign of complex tasks.

The concept of long-haul low-cost operations has become somewhat appealing in the airline industry in recent years. In Europe, the rapid expansion of low-cost carrier Norwegian that entered the long-haul markets from several large metropolises (London, Paris, Barcelona, etc.) imposed a burden of challenges to full-service carriers (FSCs). However, Norwegian operates a large portion of its long-haul service from London Gatwick by offering flights mainly on high-density routes. Although Norwegian's capacity and market shares on these routes are still at a low level mainly due to the carrier's “puppy-dog” strategy, it seems that its effect on British Airways, the dominant carrier on these markets, cannot be ignored. The purpose of the research is to examine the extent to which the presence of Norwegian affects the prices charged by British Airways on three selected high-density transatlantic routes performed from London area. The model applies simultaneous equation systems to determine how the emergence of Norwegian affects the price and the passenger volume of British Airways, as a traditionally dominant carrier, at the city-pair markets. The findings are consistent with the well-established view held in the literature, that a LCC's presence at a specific market would generally affect the incumbents to reduce their prices. Indeed, British Airways announced the capacity expansion as a counter-strategy to mitigate the competitive pressure induced by Norwegian and its affordable service.

The competition between low-cost carriers (LCC) and full-service network carriers (FSNC) has been focused exclusively on short to medium-haul markets for a long time. The launch of new aircraft generation combined with further liberalization of intercontinental air transport market presents the backbone of the recent extension of LCCs’ service into long-haul sector. Thus, the emergence of this new concept triggered the changes in the landscape of competition, since it tremendously affects the operations of incumbents, mainly FSNCs. The aim of the paper is to examine the overall profit performance of airlines with different business models (LCC vs. FSNCs) that compete in some portion of long-haul market in terms of different competitive parameters. The paper proposes the method that incorporates the major factors affecting airline profit. The method enables the construction of high level causal multidimensional plane that illustrates the behavior of profits in terms of different indicators (such as fuel costs, other operating costs excluding fuel, average stage lengths, average load factor, etc.). The conversion of these tridimensional graphs into two-dimensional one enables the researchers to easily compare the airlines’ profits under different selection of dependent variables. The results obtained in this way may have practical benefits to academics, but moreover to airline management and operations that can easily detect the major competitive advantages/disadvantages in contrast to its rival(s).

The COVID-19 pandemic posed an existential threat to European SMEs' financial resilience with significant consequences for the European economy. Using unique firm-level data on SME financing conditions, this paper proposes a new insolvency risk measure based on survey responses. We show that SME insolvency risk increased, on average, by approximately 21% during the pandemic. Problems with finding customers and the cost of production and labor contributed notably to SME insolvency risk during this period, and SMEs also saw deterioration in their access to finance. Innovation worked as a mitigating factor during the pandemic, and innovative SMEs were more resilient, maintained their client base, and saw favorable access to bank lending. Our results point out that SME innovation can prevent the number of insolvencies from rising significantly in the long term.

A lattice gas model of financial markets is presented that has the potential to explain previous empirical observations of the interplay of trends and reversion in the markets, including a Langevin equation for the time evolution of trends. In this model, the shares of an asset correspond to gas molecules that are distributed across a hidden social network of investors. Neighbors in the network tend to align their positions due to herding behavior, corresponding to an attractive force of the gas molecules. This model is equivalent to the Ising model on this network, with the magnetization in the role of the deviation of the market price of an asset from its long-term value. Moreover, in efficient markets the system should naturally drive itself to its critical temperature, where it undergoes a second-order phase transition. There, it is characterized by long-range correlations and universal critical exponents, in analogy with the phase transition between water and steam. Applying scalar field theory and the renormalization group, we show that these critical exponents imply predictions for the auto-correlations of financial market returns and for Hurst exponents. For a network topology of R^D, consistency with observation implies a fractal dimension of the network of D close to 3, and a correlation time of at least the length of the economic cycle. However, while this simplest model agrees well with market data on very long and on short time scales, it does not explain the observed market trends on intermediate time horizons from one month to one year. In a next step, the approach should therefore be extended to other models of critical dynamics, to general network topologies, and to the neighbourhood of the critical point. It allows us to indirectly measure universal properties of the hidden social network of investors from the empirically observable scaling behaviour of financial markets.

How do financial markets react to populist electoral success? Theoretically, the effect can go in one of two directions. In the first instance, populists tend to espouse resolutely anti-finance ideas, and thus a populist wave would be expected to be bad for financial returns across the board. On the other hand, populists also tend to enact various stimulus and redistributive schemes, and these policies could also give a boost to financial markets. Additionally, in the long-term, if populists become entrenched, they take over the commanding heights, meaning a need for functioning financial markets in order to provide capital for the elites. Utilizing new advances in the measurement of populism, this paper amasses a database of populist advances across developed economies since 2008 and arrays them against equity market performance. Using EGARCH-M volatility modelling on pooled data and event studies on specific episodes of populist success, this analysis reveals that a) populism's effect in the short run is mainly through volatility channels and b) populism's longer-term effects are highly dependent on the specific brand of populism and the country context in which populism operates.

What have been the determinants of financial volatility in the transition countries of Central and Eastern Europe and the former Soviet Union? This paper posits that institutional changes, and in particular the volatility of crucial institutions such as property rights, have been the major causes of financial volatility in transition. Building a unique monthly database of 20 transition economies from 1991 to 2017, this paper applies the GARCH family of models to examine financial volatility as a function of institutional volatility. The results show that more advanced institutions help to dampen financial sector volatility, while institutional volatility feeds through directly to financial sector volatility in transition. Democratic changes in particular engender much higher levels of volatility, while property rights are sensitive to the metric used for their measurement.

Monetary policies follow a complex and chaotic process, one that is enhanced when monetary growth is taken to the extreme, as in hyperinflation. While we have a basic understanding of the complex dynamics of hyperinflation, a less-explored phenomenon accompanying hyperinflationary episodes is the effect that they have on institutional development. Building on recent advances in economic history examining monetary policy and institutions, this analysis uses more explicit recourse to complexity theory and in particular complex adaptive systems to examine two separate hyperinflationary episodes in Hungary, 1923 and 1946. Delving into the institutional and cultural roots of the inflationary policies of the Hungarian government and detailing the institutional effects which succeeded hyperinflation, this paper shows that the twin experiences of Hungary were both chaotic and created a chaotic and complex aftermath, the results of which are still being felt. Indeed, Hungary's 1923 and especially its 1946 hyperinflation shows that some economic chaos cannot be restrained by political institutions and in fact the institutions themselves were changed. When staring into the abyss, Hungary also found that the abyss stared back.

Peer-to-Peer (P2P) FinTech platforms allow cost reduction and service improvement in credit lending. However, these improvements may come at the price of a worse credit risk measurement, and this can hamper lenders and endanger the stability of a financial system. We approach the problem of credit risk for Peer-to-Peer (P2P) systems by presenting a latent factor-based classification technique to divide the population into major network communities in order to estimate a more efficient logistic model. Given a number of attributes that capture firm performances in a financial system, we adopt a latent position model which allow us to distinguish between communities of connected and not-connected firms based on the spatial position of the latent factors. We show through empirical illustration that incorporating the latent factor-based classification of firms is particularly suitable as it improves the predictive performance of P2P scoring models.

The effective corporate profit tax rates (ETRs) of multinational enterprises (MNEs) are in general lower than those of national enterprises (NEs). In this paper, we argue that the bargaining power of MNEs is an important factor in explaining these differences beyond profit shifting. First, larger and more profitable firms are more valuable for tax authorities through, e.g., higher tax revenues and employment. In threatening to move their operations to other jurisdictions, larger firms, and specifically MNEs, may be able to extract greater tax deductions. This results in a regressive ETR schedule for MNEs and NEs. Second, MNEs face arguably lower costs to relocate their business (or profits) to foreign countries with a lower tax rate than NEs. This improves MNEs' threat point in bargaining and enables them further to extract higher tax deductions than NEs. To empirically quantify the importance of bargaining on the tax gap between MNEs and NEs, it is elemental to rigorously condition on the determinants of MNE status, profit taxation, as well as possible profit-shifting activities. To that end, we use French firm-level data and entropy balancing on the joint determinants of MNE status (including the possibility of profit shifting) and a firm's ETR. We find that the empirical regressivity of the French tax schedule reduces French MNEs' ETRs by 2.52 percentage points on average due to their larger size, while the relocation threat of the same firms reduces their ETR by 3.58 percentage points relative to comparable NEs. The former is a tax advantage that any firm (MNE or NE) of the same size could obtain, while the latter is specific to MNEs and beyond the reach of NEs.

Financial markets across all asset classes are known to exhibit trends, which have been exploited by traders for decades. However, a closer look at the data reveals that those trends tend to revert when they become too strong. Here, we empirically measure the interplay between trends and reversion in detail, based on 30 years of daily futures prices for equity indices, interest rates, currencies and commodities. We find that trends tend to revert before they become statistically significant. Our key observation is that tomorrow's expected return follows a cubic polynomial of today's trend strength. The positive linear term of this polynomial represents trend persistence, while its negative cubic term represents trend reversal. Their precise coe fficients determine the critical trend strength, beyond which trends tend to revert. These coefficients are small but statistically highly significant, if decades of data for many different markets are combined. We confirm this by bootstrapping and out-of-sample testing. Moreover, we find that these coefficients are universal across asset classes and have a universal scaling behavior, as the trend's time horizon runs from a few days to several years. We also measure the rate, at which trends have become less persistent, as markets have become more effi cient over the decades. Our empirical results point towards a potential deep analogy between financial markets and critical phenomena. In this analogy, the trend strength plays the role of an order parameter, whose dynamics is described by a Langevin equation. The cubic polynomial is the derivative of a quartic potential, which plays the role of the energy. This supports the conjecture that financial markets can be modeled as statistical mechanical systems near criticality, whose microscopic constituents are Buy/Sell orders.

The adoption of the euro is a crucial turning point for the economy of any EU member and the culmination of a long process of exchange rate management and macroeconomic convergence. But how does the prospect of euro area enlargement play out in the countries that have already adopted the euro? Are new members seen as a way to expand the club of like-minded countries, or are they perceived as a threat to stability, either because there exists a moral hazard risk from the side of old members to adopt riskier behavior on behalf of new members or vice versa? This paper looks at the effects of the news of the euro’s adoption event in new members on the stock returns of nineteen euro area countries, employing both an event study methodology and APARCH modeling to capture and test the form of responses of European financial market volatility. Our results show that markets were indeed pleased when new members joined the euro area, with negative responses due solely to local conditions rather than euro area-wide travails. In our most interesting finding, the expansion of the euro actually helped to dampen local market volatility in the post-crisis period in the founding member states, while euro adoption quelled volatility both pre- and post-crisis for non-founding members.

This article argues that Pippenger's (2011) "Solution to the forward-bias puzzle" must be regarded as an econometric explanation of the famous puzzle, although it does not offer an exhaustive economic answer to it. Some of Pippenger's (2011) findings are reproduced and established in a cointegrated multiple time series model. It is suggested that economists should stop trying to working out the forward-bias puzzle and start looking for fundamentally better models of foreign exchange rate determination. A tentative alternative is provided.