No caso da minha mulher também estamos à espera há cerca de 2 anos, mas os advogados avisaram-nos logo que não seriam menos de 4-5 anos para ela

Obrigado Pedro! No nosso caso nem é muito crítico pois felizmente as miúdas são americanas. Há pessoal que tem bebés apátridas por causa dos atrasos. De qualquer das formas, insólito que as minhas filhas portuguesas já tenham dois vistos de entrada em Portugal no seu passaporte

Link to the paper: s3.amazonaws.com/real.stlouis...

Once again, our method can be applied to *any* credit registry dataset that reports basic information on the characteristics of credit facilities. Such credit registries are extremely common in Europe, Latin America and parts of Asia. 11/11

We conclude by applying a back-of-the-envelope version of our method to summary stats reported in other papers in the literature that study capital allocation efficiency using data on credit. Doing it properly requires micro data, but we show our results are not crazy 10/n

This means that loans were "underpriced" during this period, i.e. contractual rates were too low given observable loan characteristics. We speculate that this could have been caused by credit market interventions, perception of implicit guarantees, and/or zombie lending 9/n

In particular, we show that the distribution of these lender discount rates becomes negatively skewed during 2020-21. This is not what we would expect from an "increasing risk premia" story, which would generate positive skew. These rates become too *low* during this period 8/n

We argue that this spike was driven by an increase in the coefficient of variation of "lender discount rates". These are the residuals of loan asset pricing: fluctuations in contractual rates that do not reflect changes in the observable terms of loans, such as maturity or PD 7/n

We find that, unexpectedly, capital misallocation is generally low in the US throughout our sample. Losses are around 0.5% of GDP. There is a large spike in 2020-21 (average of 1.1%) and then a return to normal levels 6/n

Knowledge of the social planner's marginal value of capital (r^social) allows us to estimate the extent of "static" capital misallocation using a sufficient statistics approach that relies on the first and second moments of r^social 5/n

Our method requires knowledge of i) type of loan, ii) interest rate, iii) maturity, iv) probability of default, v) loss given default. The outputs are measures of a) lender's discount rate, b) firm's internal cost of capital, c) social planner's marginal value of capital 4/n

Using a standard dynamic corporate finance model, we show how to map basic credit registry data objects into economic variables that are informative about the expected marginal revenue product of capital for firms, a key input for most measures of capital misallocation 3/n

We do two things:
1. develop a method to measure capital misallocation that can be applied to any credit registry data, using a dynamic corporate finance model as a measurement device
2. apply this method to US data, the Federal Reserve's FR Y-14Q (stress testing data) 2/n

CDS não sei, mas não há comparação possível ao PSD